Job Summary

We are seeking a talented Network Automation Engineer to design, develop, and implement automation solutions that improve the efficiency, scalability, and reliability of enterprise network infrastructure. In this role, you will automate network provisioning, configuration management, monitoring, and operational workflows across on-premises, cloud, and hybrid environments.

You will work closely with Network Engineers, Cloud Engineers, DevOps teams, and Security professionals to build Infrastructure as Code (IaC) solutions, automate repetitive tasks, and modernize network operations using programmable networking technologies. The ideal candidate has strong experience with Python, network automation frameworks, APIs, and enterprise networking technologies.

Key Responsibilities

• Design, develop, and maintain network automation solutions for enterprise infrastructure.
• Automate network configuration, provisioning, deployment, and lifecycle management.
• Develop Python scripts and automation tools to streamline daily network operations.
• Build Infrastructure as Code (IaC) solutions using Ansible, Terraform, and similar automation platforms.
• Integrate network devices with REST APIs, NETCONF, RESTCONF, and other programmable interfaces.
• Automate software upgrades, configuration backups, compliance validation, and change management.
• Develop reusable automation playbooks and workflows for network operations.
• Collaborate with Network, Cloud, DevOps, and Security teams to improve infrastructure efficiency.
• Troubleshoot network automation scripts, APIs, and deployment issues.
• Monitor automation processes and optimize performance, reliability, and scalability.
• Maintain network documentation, automation libraries, and technical standards.
• Support enterprise routing, switching, wireless, firewall, and cloud networking environments.
• Participate in disaster recovery planning and business continuity initiatives.
• Stay current with emerging networking technologies, automation frameworks, and industry best practices.

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, Network Engineering, or a related field.
• 3–6+ years of experience in enterprise networking, network engineering, or network automation.
• Strong knowledge of routing and switching technologies.
• Experience with Python scripting for network automation.
• Hands-on experience with Ansible, Terraform, or similar Infrastructure as Code tools.
• Experience using REST APIs and network programmability technologies.
• Strong understanding of TCP/IP networking, VLANs, VPNs, routing protocols, and network security.
• Experience with Linux operating systems and shell scripting.
• Excellent troubleshooting, analytical, and problem-solving skills.
• Strong communication and collaboration abilities.

Preferred Qualifications

• Experience with Cisco DNA Center, Cisco ACI, Juniper Apstra, or Arista CloudVision.
• Experience working in cloud networking environments (AWS, Microsoft Azure, or Google Cloud Platform).
• Familiarity with DevOps methodologies and CI/CD pipelines.
• Experience with Software-Defined Networking (SDN) and SD-WAN technologies.
• Knowledge of network monitoring and observability platforms.
• Experience with containerized networking and Kubernetes.
• Familiarity with Zero Trust networking and network security automation.

Technical Skills

Programming & Automation

• Python
• Bash
• PowerShell
• Ansible
• Terraform
• Git
• YAML
• JSON

Networking Technologies

• TCP/IP
• LAN/WAN
• VLAN
• VPN
• MPLS
• SD-WAN
• DNS
• DHCP
• NAT
• QoS

Routing & Switching

• Cisco IOS
• Cisco NX-OS
• Juniper Junos
• Arista EOS
• BGP
• OSPF
• EIGRP
• STP

Network Programmability

• REST APIs
• NETCONF
• RESTCONF
• gNMI
• YANG Models
• Cisco DNA Center API
• Cisco Meraki API

Cloud Networking

• AWS VPC
• Microsoft Azure Virtual Network
• Google Cloud VPC
• Hybrid Cloud Networking
• VPN Gateway
• Direct Connect
• ExpressRoute

Monitoring & Observability

• SolarWinds
• Grafana
• Prometheus
• Splunk
• Wireshark
• Nagios
• ThousandEyes

Operating Systems

• Linux
• Windows Server

Version Control & DevOps

• Git
• GitHub
• GitLab
• Jenkins
• CI/CD Pipelines

Preferred Certifications

• Cisco Certified Network Professional (CCNP Enterprise)
• Cisco Certified DevNet Professional
• Cisco Certified DevNet Associate
• Juniper Networks Certified Professional (JNCIP)
• AWS Certified Advanced Networking – Specialty
• HashiCorp Terraform Associate
• Red Hat Certified System Administrator (RHCSA)
• Microsoft Certified: Azure Network Engineer Associate

Soft Skills

• Strong analytical and problem-solving abilities
• Excellent verbal and written communication skills
• Ability to work in cross-functional teams
• Project planning and time management
• Attention to detail and documentation
• Adaptability in fast-paced environments
• Continuous learning mindset
• Customer-focused approach

Benefits

• Competitive salary with annual performance bonus
• Medical, dental, and vision insurance
• Flexible remote and hybrid work options
• Paid vacation, holidays, and sick leave
• Paid parental leave
• Professional certification reimbursement
• Learning and development budget
• Employee stock purchase plan or equity (where applicable)
• Wellness and employee assistance programs
• Career growth and leadership development opportunities

Job Summary

We are seeking an experienced Senior Data Scientist to join our growing Data Science and Artificial Intelligence team. In this role, you will leverage advanced analytics, statistical modeling, and machine learning to solve complex business problems and drive strategic decision-making. You will work with large-scale structured and unstructured datasets to build predictive models, develop AI-powered solutions, and deliver actionable insights that support business growth.

As a Senior Data Scientist, you will collaborate closely with data engineers, software developers, product managers, business stakeholders, and executive leadership to transform data into innovative products and measurable business value. The ideal candidate has strong technical expertise in machine learning, statistical analysis, programming, cloud platforms, and data visualization, along with excellent communication and leadership skills.

Key Responsibilities

• Design, develop, and deploy predictive, statistical, and machine learning models to solve business challenges.
• Analyze large, complex datasets to identify trends, patterns, and actionable insights.
• Build forecasting, recommendation, classification, clustering, and optimization models.
• Perform exploratory data analysis (EDA), feature engineering, and data preprocessing.
• Develop scalable data science solutions that support production applications.
• Evaluate and improve machine learning model performance using appropriate metrics and validation techniques.
• Partner with Data Engineering teams to develop reliable data pipelines and ensure data quality.
• Collaborate with Product Managers, Software Engineers, and business stakeholders to understand business requirements and translate them into analytical solutions.
• Present findings and recommendations to technical and non-technical audiences, including executive leadership.
• Build dashboards, reports, and visualizations that communicate business insights effectively.
• Implement model monitoring processes to detect model drift and maintain production performance.
• Support A/B testing, experimentation, and causal inference analyses to optimize products and business strategies.
• Mentor junior Data Scientists and contribute to technical best practices across the team.
• Stay current with emerging technologies, AI trends, machine learning techniques, and industry best practices.
• Maintain documentation for models, experiments, methodologies, and technical solutions.

Required Qualifications

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Artificial Intelligence, Engineering, or a related field.
• 4–8+ years of professional experience in Data Science, Machine Learning, or Advanced Analytics.
• Strong expertise in statistical analysis, predictive modeling, and machine learning algorithms.
• Experience working with large-scale datasets and distributed computing frameworks.
• Proficiency in Python and SQL for data analysis and model development.
• Experience deploying machine learning models into production environments.
• Strong understanding of cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
• Excellent problem-solving, analytical thinking, and communication skills.
• Ability to work independently and collaboratively in cross-functional teams.

Preferred Qualifications

• Master's degree or Ph.D. in Data Science, Artificial Intelligence, Statistics, Computer Science, or a related field.
• Experience with Generative AI, Large Language Models (LLMs), or Retrieval-Augmented Generation (RAG).
• Experience with MLOps and machine learning deployment pipelines.
• Knowledge of data governance, responsible AI, and model explainability.
• Experience working in Agile software development environments.
• Prior experience mentoring technical team members or leading data science initiatives.

Technical Skills

Programming Languages

• Python
• SQL
• R (Preferred)
• Scala (Preferred)

Machine Learning & AI

• Supervised Learning
• Unsupervised Learning
• Deep Learning
• Reinforcement Learning
• Natural Language Processing (NLP)
• Computer Vision
• Time Series Forecasting
• Recommendation Systems
• Generative AI
• Large Language Models (LLMs)

Data Science Libraries

• Scikit-learn
• TensorFlow
• PyTorch
• XGBoost
• LightGBM
• Pandas
• NumPy
• SciPy

Data Visualization

• Tableau
• Microsoft Power BI
• Matplotlib
• Plotly

Big Data Technologies

• Apache Spark
• Hadoop
• Databricks
• Snowflake

Cloud Platforms

• Amazon Web Services (AWS)
• Microsoft Azure
• Google Cloud Platform (GCP)

Databases

• PostgreSQL
• MySQL
• SQL Server
• MongoDB

Tools

• Git
• Docker
• Kubernetes
• MLflow
• Airflow
• Jupyter Notebook

Preferred Certifications

• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure Data Scientist Associate
• Google Professional Machine Learning Engineer
• Databricks Certified Machine Learning Professional
• TensorFlow Developer Certificate
• SAS Certified Data Scientist

Soft Skills

• Strong analytical and critical thinking abilities
• Excellent verbal and written communication
• Leadership and mentoring capabilities
• Business problem-solving mindset
• Collaboration across cross-functional teams
• Time management and project prioritization
• Adaptability in fast-paced environments
• Strong presentation and stakeholder management skills

Benefits

• Competitive salary with annual performance bonus
• Comprehensive medical, dental, and vision insurance
• Flexible remote and hybrid work options
• Paid vacation, holidays, and sick leave
• Paid parental leave
• Employee stock purchase plan or equity (where applicable)
• Learning and development budget
• Certification reimbursement
• Wellness and mental health programs
• Career advancement opportunities
• Collaborative and inclusive work environment

Job Description

We are seeking an innovative AI Security Engineer to safeguard our artificial intelligence and machine learning platforms from evolving cyber threats. In this role, you will design and implement security controls for AI systems, large language models (LLMs), machine learning pipelines, and cloud-native AI applications. You will work closely with AI researchers, software engineers, cloud architects, and security teams to ensure AI solutions are secure, compliant, resilient, and trustworthy throughout the development lifecycle.

The ideal candidate has strong expertise in cybersecurity, cloud security, AI/ML technologies, secure software development, and modern security frameworks. Experience securing generative AI applications, mitigating prompt injection attacks, protecting training data, and implementing AI governance is highly desirable.

Key Responsibilities

• Design, implement, and maintain security architectures for AI and machine learning systems.
• Secure Large Language Model (LLM) applications against prompt injection, jailbreak attempts, model manipulation, and data leakage.
• Perform security assessments, penetration testing, and threat modeling for AI applications and APIs.
• Protect machine learning pipelines from adversarial attacks, model poisoning, model inversion, and data poisoning.
• Build automated security controls for MLOps and AI deployment pipelines.
• Collaborate with development teams to integrate security into AI application development using DevSecOps best practices.
• Implement Identity and Access Management (IAM) controls for AI platforms and cloud environments.
• Monitor AI infrastructure for suspicious activity, vulnerabilities, and security incidents.
• Develop detection rules and incident response playbooks for AI-specific cyber threats.
• Conduct AI risk assessments and recommend mitigation strategies.
• Ensure compliance with industry standards, privacy regulations, and AI governance policies.
• Research emerging AI threats and recommend proactive security improvements.
• Perform security code reviews and vulnerability assessments for AI-powered applications.
• Work with cloud teams to secure AI workloads deployed on AWS, Azure, or Google Cloud.
• Create technical documentation, security reports, and security awareness materials for AI development teams.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Cybersecurity, Artificial Intelligence, Information Technology, or a related field.
• 3–7+ years of experience in cybersecurity, cloud security, application security, or AI security.
• Experience with AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Strong understanding of cybersecurity principles, secure coding practices, and threat modeling.
• Experience securing cloud environments (AWS, Azure, or Google Cloud Platform).
• Knowledge of MLOps pipelines and CI/CD security.
• Familiarity with AI governance, privacy, and regulatory compliance.
• Strong scripting or programming skills in Python, Java, or Go.
• Excellent analytical, problem-solving, and communication skills.

Preferred Skills

• AI Security
• Large Language Models (LLMs)
• Prompt Injection Defense
• Adversarial Machine Learning
• Machine Learning Security
• MLOps
• DevSecOps
• Cloud Security (AWS, Azure, GCP)
• Kubernetes
• Docker
• Terraform
• Python
• TensorFlow
• PyTorch
• SIEM (Splunk, Microsoft Sentinel)
• MITRE ATT&CK
• Zero Trust Architecture
• Identity & Access Management (IAM)
• API Security
• Threat Intelligence
• Incident Response
• Vulnerability Management
• Secure Software Development Lifecycle (SSDLC)

Preferred Certifications

• Certified Information Systems Security Professional (CISSP)
• GIAC Certified Incident Handler (GCIH)
• GIAC Cloud Security Automation (GCSA)
• AWS Certified Security – Specialty
• Microsoft Certified: Azure Security Engineer Associate
• Certified Cloud Security Professional (CCSP)
• Offensive Security Certified Professional (OSCP) (preferred for offensive AI security testing)

Benefits

• Competitive salary and annual performance bonus
• Comprehensive medical, dental, and vision insurance
• Flexible remote and hybrid work options
• Paid vacation, holidays, and parental leave
• Professional development and certification reimbursement
• Learning budget for AI and cybersecurity training
• Employee stock purchase or equity program (where applicable)
• Wellness and employee assistance programs

Job Description

We are seeking a highly skilled Applied AI Scientist to join our Artificial Intelligence team and develop innovative AI solutions that address complex business and customer challenges. In this role, you will research, design, develop, and deploy advanced machine learning and Generative AI models into production environments. You will work with cross-functional teams to transform cutting-edge AI research into scalable, real-world applications across industries such as finance, healthcare, retail, cybersecurity, manufacturing, and enterprise software.

The ideal candidate has strong expertise in machine learning, deep learning, natural language processing (NLP), computer vision, Large Language Models (LLMs), and cloud-based AI platforms. You will play a key role in building AI-powered products, improving business processes, and driving innovation through data-driven decision-making.

Key Responsibilities

• Design, develop, and deploy advanced machine learning and deep learning models for real-world business applications.
• Build and optimize Generative AI solutions using Large Language Models (LLMs) and foundation models.
• Develop Retrieval-Augmented Generation (RAG) pipelines to enhance AI application accuracy and knowledge retrieval.
• Fine-tune, evaluate, and optimize pre-trained AI models for performance, scalability, and reliability.
• Analyze structured and unstructured datasets to extract actionable insights and support strategic business decisions.
• Collaborate with product managers, software engineers, data scientists, and AI researchers to deliver production-ready AI solutions.
• Implement AI model monitoring, evaluation, and continuous improvement processes.
• Develop feature engineering pipelines, model validation frameworks, and experimentation methodologies.
• Integrate AI models into cloud-native applications and enterprise systems using scalable APIs and MLOps practices.
• Conduct research on emerging AI technologies and recommend innovative solutions.
• Ensure AI systems adhere to responsible AI principles, fairness, explainability, security, and regulatory compliance.
• Document technical designs, research findings, and model performance metrics.
• Mentor junior data scientists and machine learning engineers while promoting AI best practices across teams.

Required Qualifications

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, Mathematics, or a related field.
• 5+ years of experience developing and deploying machine learning or AI solutions.
• Strong expertise in supervised, unsupervised, and deep learning techniques.
• Hands-on experience with Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
• Proficiency in Python and experience with TensorFlow, PyTorch, or JAX.
• Strong understanding of statistics, optimization, probability, and linear algebra.
• Experience deploying AI models in cloud environments (AWS, Microsoft Azure, or Google Cloud Platform).
• Excellent problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with multimodal AI systems and AI agents.
• Familiarity with reinforcement learning and AI model evaluation.
• Knowledge of MLOps, CI/CD pipelines, and containerized deployments.
• Experience with vector databases and semantic search technologies.
• Published AI research papers or contributions to open-source AI projects.
• Experience working with distributed machine learning systems and GPU-based training.

Technical Skills

Programming Languages

• Python
• SQL
• C++
• Java
• Scala

AI & Machine Learning

• Machine Learning
• Deep Learning
• Generative AI
• Large Language Models (LLMs)
• Natural Language Processing (NLP)
• Computer Vision
• Reinforcement Learning
• Retrieval-Augmented Generation (RAG)
• Prompt Engineering
• AI Agents

Frameworks & Libraries

• TensorFlow
• PyTorch
• JAX
• Hugging Face Transformers
• LangChain
• LlamaIndex
• Scikit-learn
• XGBoost
• MLflow

Cloud & Infrastructure

• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)
• Docker
• Kubernetes
• Databricks
• Apache Spark

Databases & Tools

• Pinecone
• Weaviate
• ChromaDB
• PostgreSQL
• Git
• REST APIs

Preferred Certifications

• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate
• Databricks Certified Machine Learning Professional
• TensorFlow Developer Certificate

Soft Skills

• Analytical Thinking
• Innovation and Research
• Critical Problem Solving
• Technical Communication
• Cross-Functional Collaboration
• Leadership and Mentoring
• Strategic Thinking
• Continuous Learning
• Business Acumen
• Project Management

Career Growth

• Senior Applied AI Scientist
• Principal AI Scientist
• Staff AI Scientist
• AI Research Scientist
• AI Solutions Architect
• Director of Artificial Intelligence
• Vice President of AI
• Chief AI Officer (CAIO)

Job Description

We are seeking an innovative Machine Learning Research Scientist to join our AI Research team and drive the development of next-generation machine learning technologies. In this role, you will conduct advanced research, design state-of-the-art algorithms, and develop scalable AI models that solve complex real-world problems across domains such as natural language processing (NLP), computer vision, recommendation systems, predictive analytics, and generative AI.

You will collaborate with data scientists, software engineers, research scientists, and product teams to transform cutting-edge research into production-ready AI solutions. The ideal candidate has a strong background in machine learning, deep learning, mathematics, and large-scale data analysis, with a passion for innovation and scientific discovery.

Key Responsibilities

• Conduct advanced research in machine learning, deep learning, and artificial intelligence.
• Design, develop, and evaluate novel machine learning algorithms and models.
• Build and optimize large-scale predictive and generative AI models.
• Research and improve Large Language Models (LLMs), foundation models, and multimodal AI systems.
• Develop scalable AI solutions for NLP, computer vision, recommendation systems, and time-series forecasting.
• Perform statistical analysis, feature engineering, and model experimentation.
• Design and execute research experiments to validate model performance.
• Collaborate with engineering teams to deploy machine learning models into production.
• Publish research papers, technical reports, patents, and conference presentations.
• Stay current with the latest advancements in AI, machine learning, and data science.
• Mentor junior researchers and data scientists.
• Ensure AI models are accurate, reliable, scalable, and ethically developed.

Required Qualifications

• Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Statistics, Mathematics, or a related field.
• 5+ years of experience in machine learning research or applied AI.
• Strong knowledge of supervised, unsupervised, reinforcement, and deep learning techniques.
• Experience with large-scale datasets and distributed machine learning systems.
• Proficiency in Python and ML frameworks such as TensorFlow or PyTorch.
• Strong mathematical foundation in linear algebra, probability, optimization, and statistics.
• Experience publishing research papers or contributing to open-source AI projects is preferred.
• Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience with Generative AI and Large Language Models (LLMs).
• Knowledge of reinforcement learning and multimodal AI.
• Experience with cloud platforms (AWS, Azure, or Google Cloud).
• Familiarity with MLOps and model deployment.
• Experience with distributed training and GPU computing.
• Publications in leading AI conferences (NeurIPS, ICML, ICLR, CVPR, ACL, etc.).
• Experience with responsible AI and model governance.

Technical Skills

Programming Languages

• Python
• C++
• Java
• Scala
• SQL

Machine Learning & AI

• Machine Learning
• Deep Learning
• Generative AI
• Large Language Models (LLMs)
• Reinforcement Learning
• Natural Language Processing (NLP)
• Computer Vision
• Recommendation Systems
• Time-Series Forecasting

Frameworks & Libraries

• TensorFlow
• PyTorch
• Scikit-learn
• Hugging Face Transformers
• XGBoost
• LightGBM
• MLflow

Data & Cloud Technologies

• Apache Spark
• Databricks
• Snowflake
• Docker
• Kubernetes
• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)

Data Visualization

• Tableau
• Power BI
• Matplotlib
• Plotly

Preferred Certifications

• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate
• TensorFlow Developer Certificate
• Databricks Certified Machine Learning Professional

Soft Skills

• Critical Thinking
• Research & Innovation
• Scientific Problem Solving
• Analytical Thinking
• Collaboration
• Technical Writing
• Presentation Skills
• Leadership
• Mentoring
• Continuous Learning

Career Growth

• Senior Machine Learning Research Scientist
• Principal Machine Learning Scientist
• Distinguished AI Scientist
• AI Research Lead
• Director of AI Research
• Head of Machine Learning
• Vice President of AI
• Chief AI Officer (CAIO)

Job Summary

We are seeking an innovative Cybersecurity Research Scientist to join our advanced security research team. In this role, you will conduct cutting-edge research to identify emerging cyber threats, develop next-generation defense techniques, and improve the security of enterprise systems, cloud platforms, artificial intelligence (AI), and critical infrastructure.

You will collaborate with security engineers, data scientists, software developers, and threat intelligence teams to create novel cybersecurity solutions, publish technical research, and translate research findings into practical security technologies. This position is ideal for candidates passionate about solving complex security challenges through scientific research, experimentation, and innovation.

Key Responsibilities

• Conduct advanced research on emerging cyber threats, attack techniques, and security vulnerabilities.
• Design and develop innovative cybersecurity solutions using artificial intelligence, machine learning, and data analytics.
• Perform malware analysis, reverse engineering, and exploit research.
• Research adversarial AI, model security, and AI-driven cyber defense strategies.
• Develop threat detection algorithms and behavioral analytics models.
• Create proof-of-concept security tools, prototypes, and research frameworks.
• Publish technical papers, white papers, patents, and security research reports.
• Collaborate with software engineering teams to integrate research findings into production security solutions.
• Analyze zero-day vulnerabilities and emerging attack vectors.
• Conduct penetration testing research and exploit development for defensive purposes.
• Evaluate new security technologies, frameworks, and industry standards.
• Participate in threat hunting, digital forensics, and incident investigations.
• Present research findings at conferences, internal technical forums, and customer briefings.
• Mentor junior researchers and security engineers.
• Stay current with the latest cybersecurity trends, academic research, and global threat intelligence.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Cybersecurity, Information Security, Software Engineering, or a related field.
• Ph.D. preferred for advanced research positions.
• 5+ years of experience in cybersecurity research, security engineering, or applied security.
• Strong understanding of operating systems, networking, and distributed systems.
• Experience conducting security research and vulnerability analysis.
• Proficiency in Python, C++, Rust, Go, or Java.
• Experience with Linux, Windows, and cloud environments.
• Strong analytical, problem-solving, and research skills.
• Excellent technical writing and presentation abilities.

Preferred Qualifications

• Experience with AI/ML security research.
• Knowledge of cloud security (AWS, Azure, Google Cloud).
• Familiarity with Kubernetes and container security.
• Experience in malware reverse engineering.
• Knowledge of cryptography and secure protocol design.
• Contributions to open-source security projects.
• Published cybersecurity research papers or patents.
• Experience working in research labs or advanced security teams.

Technical Skills

Programming Languages

• Python
• C++
• Go
• Rust
• Java
• Bash
• PowerShell

Cybersecurity

• Threat Intelligence
• Threat Hunting
• Digital Forensics
• Malware Analysis
• Reverse Engineering
• Vulnerability Research
• Incident Response
• Secure Software Development
• Adversarial AI
• Security Automation

Cloud & Infrastructure

• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)
• Docker
• Kubernetes
• Terraform

AI & Data Science

• Machine Learning
• Deep Learning
• TensorFlow
• PyTorch
• Scikit-learn
• Large Language Model (LLM) Security
• AI Model Evaluation

Security Tools

• Splunk
• Microsoft Sentinel
• CrowdStrike Falcon
• Palo Alto Cortex XDR
• Wireshark
• Burp Suite
• Metasploit
• Ghidra
• IDA Pro
• YARA
• Sigma Rules

Preferred Certifications

• CISSP (Certified Information Systems Security Professional)
• GIAC Reverse Engineering Malware (GREM)
• GIAC Certified Incident Handler (GCIH)
• GIAC Certified Forensic Analyst (GCFA)
• Certified Ethical Hacker (CEH)
• Offensive Security Certified Professional (OSCP)
• AWS Certified Security – Specialty
• Microsoft Certified: Cybersecurity Architect Expert

Soft Skills

• Critical Thinking
• Research & Innovation
• Analytical Problem Solving
• Technical Communication
• Collaboration
• Leadership
• Creativity
• Scientific Writing
• Project Management
• Continuous Learning

Career Growth

• Senior Cybersecurity Research Scientist
• Principal Research Scientist
• Distinguished Security Researcher
• Security Architect
• AI Security Architect
• Director of Cybersecurity Research
• Chief Security Scientist
• Chief Information Security Officer (CISO

Job Description

We are seeking an experienced AI Ethics & Responsible AI Specialist to help ensure that our artificial intelligence and machine learning solutions are developed, deployed, and governed responsibly. This role is responsible for establishing ethical AI practices, assessing AI risks, and implementing governance frameworks that promote fairness, transparency, accountability, privacy, and regulatory compliance across AI initiatives.

The ideal candidate will work closely with AI Engineers, Data Scientists, Product Managers, Legal, Security, Privacy, and Compliance teams to evaluate AI systems throughout their lifecycle. You will help identify and mitigate algorithmic bias, improve model explainability, develop AI governance policies, and ensure compliance with emerging AI regulations and industry standards.

This position requires a strong understanding of machine learning, AI governance, risk management, data privacy, and ethical AI principles, along with the ability to communicate complex technical and regulatory concepts to both technical and business stakeholders.

Key Responsibilities

• Develop and maintain Responsible AI governance frameworks, policies, and standards.
• Conduct AI risk assessments throughout the AI and machine learning lifecycle.
• Evaluate AI models for fairness, bias, transparency, robustness, explainability, and accountability.
• Collaborate with AI Engineering and Data Science teams to implement ethical AI best practices.
• Perform algorithmic bias testing and recommend mitigation strategies.
• Ensure compliance with AI regulations, privacy laws, and industry standards.
• Develop AI model documentation, model cards, and governance reports.
• Support AI audits, regulatory assessments, and internal compliance reviews.
• Establish AI monitoring processes for model performance, drift, fairness, and compliance.
• Work with Legal, Privacy, Security, and Risk teams to evaluate AI-related risks.
• Define AI governance controls for Generative AI, Large Language Models (LLMs), and AI-powered products.
• Promote responsible data collection, usage, and retention practices.
• Deliver Responsible AI awareness sessions and training programs for technical and business teams.
• Research emerging AI regulations, governance frameworks, and ethical AI trends.
• Recommend continuous improvements to strengthen organizational AI governance and compliance.

Required Qualifications

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Information Systems, Cybersecurity, Ethics, Public Policy, Law, or a related field.
• 3–6+ years of experience in AI governance, Responsible AI, machine learning, data science, risk management, cybersecurity, compliance, or technology governance.
• Strong understanding of machine learning concepts and AI development lifecycle.
• Experience with AI governance frameworks, AI risk management, or model governance.
• Knowledge of AI fairness, explainability, model validation, and algorithmic bias mitigation techniques.
• Familiarity with AI regulations, data privacy requirements, and enterprise compliance programs.
• Excellent communication, analytical, documentation, and stakeholder management skills.
• Experience working with cross-functional teams in enterprise environments.

Preferred Qualifications

• Master's degree in Artificial Intelligence, Data Science, Computer Science, Public Policy, Ethics, or a related field.
• Experience with Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
• Experience supporting AI governance for cloud-based AI platforms.
• Familiarity with AI model lifecycle management and MLOps.
• Knowledge of enterprise risk management and cybersecurity governance.
• Experience participating in AI ethics committees or governance boards.

Preferred Technical Skills

• Python
• SQL
• Machine Learning
• Deep Learning
• Generative AI
• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• LangChain
• Hugging Face Transformers
• TensorFlow
• PyTorch
• Scikit-learn
• MLflow
• AI Governance
• Responsible AI
• Model Risk Management
• AI Fairness & Bias Detection
• Explainable AI (XAI)
• AI Model Validation
• Data Privacy
• Risk Assessment
• Governance, Risk & Compliance (GRC)
• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)
• Git
• Docker
• Kubernetes

Preferred Certifications

• Microsoft Certified: Azure AI Engineer Associate
• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Certified Information Systems Security Professional (CISSP)
• Certified Information Security Manager (CISM)
• ISO/IEC 42001 AI Management Systems (awareness or lead implementer)
• NIST AI Risk Management Framework (AI RMF) knowledge
• Certified Data Privacy Solutions Engineer (CDPSE)

Job Description

We are seeking a highly analytical and results-driven Customer Analytics Data Scientist to join our growing Data Science team. In this role, you will leverage advanced analytics, machine learning, and statistical modeling to understand customer behavior, improve customer experiences, and drive strategic business decisions. You will work closely with Product, Marketing, Sales, Customer Success, and Engineering teams to transform large datasets into actionable insights that enhance customer acquisition, engagement, retention, and lifetime value.

The ideal candidate has strong expertise in predictive analytics, customer segmentation, recommendation systems, experimentation, and data visualization. You should be proficient in Python, SQL, machine learning, and cloud-based analytics platforms, with the ability to communicate complex analytical findings to both technical and non-technical stakeholders.

Key Responsibilities

• Analyze large-scale customer data to identify trends, behaviors, and business opportunities.
• Develop predictive models for customer acquisition, retention, churn prediction, and lifetime value (CLV).
• Build customer segmentation models using clustering and behavioral analytics techniques.
• Design, execute, and evaluate A/B tests and multivariate experiments to optimize customer experiences.
• Develop recommendation systems and personalization models to improve customer engagement.
• Create forecasting models for customer demand, revenue, and marketing performance.
• Collaborate with Product, Marketing, Sales, and Customer Success teams to support data-driven decision-making.
• Design interactive dashboards and reports using business intelligence tools.
• Build and maintain scalable data pipelines for analytics and machine learning workflows.
• Apply statistical analysis and hypothesis testing to validate business initiatives.
• Monitor model performance, accuracy, and business impact, making improvements as needed.
• Ensure data quality, governance, privacy, and compliance with organizational policies.
• Present analytical findings and strategic recommendations to business leaders and executive stakeholders.
• Stay current with emerging technologies, machine learning techniques, and customer analytics best practices.

Required Qualifications

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Economics, Information Systems, or a related field.
• 3–5+ years of experience in data science, customer analytics, business analytics, or predictive modeling.
• Strong programming experience with Python and SQL.
• Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch.
• Solid understanding of statistics, predictive modeling, clustering, classification, regression, and time-series analysis.
• Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Familiarity with ETL processes, data warehousing, and big data technologies.
• Excellent analytical thinking, problem-solving, and communication skills.
• Ability to explain technical concepts and analytical insights to non-technical audiences.

Preferred Qualifications

• Master's degree in Data Science, Statistics, Computer Science, Business Analytics, or a related field.
• Experience with customer relationship management (CRM) analytics.
• Knowledge of recommendation engines and personalization algorithms.
• Experience with marketing analytics and digital customer journey analysis.
• Familiarity with MLOps tools and model deployment pipelines.
• Experience working in e-commerce, SaaS, fintech, retail, healthcare, or consumer technology industries.

Preferred Technical Skills

• Python
• SQL
• R
• Pandas
• NumPy
• Scikit-learn
• TensorFlow
• PyTorch
• Apache Spark
• Databricks
• Snowflake
• Tableau
• Power BI
• Looker
• Google Analytics 4 (GA4)
• Customer Data Platforms (CDPs)
• CRM Analytics
• Machine Learning
• Predictive Analytics
• Customer Segmentation
• Churn Prediction
• Customer Lifetime Value (CLV)
• Recommendation Systems
• A/B Testing
• Statistical Analysis
• Data Visualization
• Feature Engineering
• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)
• Git
• Docker

Job Description

We are seeking a detail-oriented Cybersecurity Compliance Analyst to join our growing cybersecurity team. The Cybersecurity Compliance Analyst is responsible for ensuring that the organization's information security practices comply with industry regulations, cybersecurity frameworks, and internal security policies. This role works closely with Security, IT, Risk Management, Legal, and Audit teams to assess compliance requirements, identify security gaps, and implement effective controls that protect organizational data and systems.

The ideal candidate has a strong understanding of cybersecurity governance, risk management, compliance frameworks, and regulatory standards such as NIST Cybersecurity Framework (CSF), NIST 800-53, ISO/IEC 27001, SOC 2, HIPAA, PCI DSS, CIS Controls, and GDPR. This position plays a critical role in supporting security audits, managing risk assessments, maintaining documentation, and driving continuous compliance initiatives across cloud and enterprise environments.

Key Responsibilities

• Conduct cybersecurity compliance assessments across enterprise and cloud environments.
• Ensure compliance with security frameworks, including NIST CSF, NIST 800-53, ISO/IEC 27001, SOC 2, PCI DSS, HIPAA, CIS Controls, and GDPR.
• Perform security risk assessments and identify compliance gaps.
• Develop, review, and maintain information security policies, standards, procedures, and documentation.
• Coordinate internal and external cybersecurity audits and regulatory assessments.
• Track remediation activities and verify the implementation of corrective actions.
• Collaborate with IT, Security Operations, Cloud, Infrastructure, and Development teams to ensure security controls are effectively implemented.
• Monitor changes in cybersecurity laws, regulations, and industry best practices.
• Maintain Governance, Risk, and Compliance (GRC) platforms and compliance dashboards.
• Prepare compliance reports, audit evidence, and executive-level presentations.
• Support third-party vendor security assessments and risk evaluations.
• Assist with security awareness initiatives and compliance training programs.
• Evaluate technical and administrative security controls for effectiveness.
• Support business continuity, disaster recovery, and cybersecurity governance initiatives.
• Recommend process improvements to strengthen the organization's security posture and regulatory compliance.

Required Qualifications

• Bachelor's degree in Cybersecurity, Information Security, Computer Science, Information Technology, or a related field.
• 2–5+ years of experience in cybersecurity, information security, risk management, governance, or compliance.
• Strong knowledge of cybersecurity governance and regulatory compliance frameworks.
• Experience supporting security audits and compliance assessments.
• Familiarity with cloud security platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Understanding of Identity and Access Management (IAM), vulnerability management, encryption, endpoint security, and security monitoring.
• Experience with Governance, Risk, and Compliance (GRC) tools.
• Excellent analytical, documentation, and communication skills.
• Ability to manage multiple compliance projects in a fast-paced environment.

Preferred Certifications

• Certified Information Systems Security Professional (CISSP)
• Certified Information Security Manager (CISM)
• Certified in Risk and Information Systems Control (CRISC)
• Certified Information Systems Auditor (CISA)
• CompTIA Security+
• ISO/IEC 27001 Lead Implementer or Lead Auditor
• Certified Cloud Security Professional (CCSP)

Preferred Technical Skills

• Governance, Risk, and Compliance (GRC)
• NIST CSF & NIST 800-53
• ISO/IEC 27001
• SOC 2
• HIPAA
• PCI DSS
• CIS Controls
• GDPR
• Cloud Security (AWS, Azure, GCP)
• Identity and Access Management (IAM)
• Risk Assessment
• Vulnerability Management
• Microsoft Defender
• Microsoft Sentinel
• Splunk
• ServiceNow GRC
• Archer GRC
• Audit Documentation
• Security Policies & Standards

Job Summary

We are seeking a talented AI Infrastructure Engineer to design, build, and optimize the cloud infrastructure that powers next-generation artificial intelligence and machine learning workloads. In this role, you will develop scalable GPU-based infrastructure, automate AI platform operations, and ensure high availability for large-scale model training and inference.

You will collaborate with AI researchers, Machine Learning Engineers, Platform Engineers, and DevOps teams to create secure, high-performance infrastructure supporting foundation models, Large Language Models (LLMs), computer vision, and generative AI applications.

Key Responsibilities

• Design, deploy, and maintain scalable AI infrastructure for machine learning and deep learning workloads.
• Build and optimize GPU clusters for AI model training and inference.
• Develop Infrastructure as Code (IaC) using tools such as Terraform and Ansible.
• Manage Kubernetes clusters and containerized AI workloads using Docker.
• Automate infrastructure provisioning, deployment, and monitoring.
• Optimize storage, networking, and compute resources for AI applications.
• Implement CI/CD pipelines for AI and machine learning platforms.
• Monitor infrastructure performance, availability, and resource utilization.
• Troubleshoot infrastructure, networking, and distributed computing issues.
• Collaborate with Machine Learning Engineers to support model deployment and lifecycle management.
• Implement security best practices, identity management, and access controls.
• Configure monitoring and logging using Prometheus, Grafana, and ELK Stack.
• Support distributed AI training frameworks and high-performance computing (HPC) environments.
• Ensure platform scalability, reliability, disaster recovery, and business continuity.
• Evaluate and adopt emerging cloud and AI infrastructure technologies.

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, Software Engineering, or a related technical field.
• 4+ years of experience in cloud infrastructure, platform engineering, DevOps, or AI infrastructure.
• Strong experience with Kubernetes, Docker, and container orchestration.
• Experience with AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Knowledge of GPU computing, NVIDIA CUDA, and AI accelerator technologies.
• Experience with Infrastructure as Code (Terraform, CloudFormation, or Ansible).
• Strong Linux system administration and networking skills.
• Experience building CI/CD pipelines using GitHub Actions, Jenkins, or GitLab CI/CD.
• Familiarity with distributed computing and machine learning infrastructure.
• Strong scripting skills in Python, Bash, or Go.
• Excellent analytical, troubleshooting, and communication skills.

Preferred Qualifications

• Experience supporting Large Language Models (LLMs) and Generative AI workloads.
• Experience with distributed training frameworks such as PyTorch Distributed, Ray, or DeepSpeed.
• Knowledge of MLOps tools including MLflow, Kubeflow, and Airflow.
• Experience with NVIDIA DGX systems or GPU clusters.
• Familiarity with vector databases and Retrieval-Augmented Generation (RAG) architectures.
• AWS Certified Solutions Architect, Google Professional Cloud Architect, or Certified Kubernetes Administrator (CKA).
• Experience with high-performance computing (HPC) environments.

Technical Skills

Cloud Platforms

• Amazon Web Services (AWS)
• Microsoft Azure
• Google Cloud Platform (GCP)

AI & Machine Learning Infrastructure

• GPU Computing
• NVIDIA CUDA
• NVIDIA DGX
• TensorRT
• Distributed Training
• MLOps
• Large Language Models (LLMs)
• Generative AI
• AI Model Deployment

Containerization & Orchestration

• Kubernetes
• Docker
• Helm
• OpenShift

Infrastructure as Code (IaC)

• Terraform
• Ansible
• CloudFormation

DevOps & CI/CD

• GitHub Actions
• GitLab CI/CD
• Jenkins
• Argo CD

Monitoring & Observability

• Prometheus
• Grafana
• ELK Stack (Elasticsearch, Logstash, Kibana)
• OpenTelemetry

Programming Languages

• Python
• Go
• Bash
• YAML

Databases & Storage

• PostgreSQL
• Redis
• MongoDB
• Amazon S3
• MinIO

Networking

• TCP/IP
• DNS
• VPN
• Load Balancing
• Network Security

Soft Skills

• Problem Solving
• Critical Thinking
• Team Collaboration
• Communication Skills
• Project Management
• Adaptability
• Time Management
• Innovation Mindset
• Leadership
• Continuous Learning

Benefits

• Competitive Base Salary
• Annual Performance Bonus
• Equity/Long-Term Incentive Eligibility
• Medical, Dental, and Vision Insurance
• Flexible Remote/Hybrid Work Options
• Paid Time Off (PTO)
• Paid Holidays
• Professional Certification Reimbursement
• Learning and Development Programs
• Wellness Programs
• Employee Assistance Program (EAP)
• Parental Leave
• Life and Disability Insurance

Job Summary

NVIDIA is seeking a highly motivated Data Science Research Scientist to join its AI Research organization. In this role, you will conduct cutting-edge research in machine learning, deep learning, generative AI, and large-scale data analytics to develop innovative algorithms that power next-generation AI products and platforms.

You will collaborate with world-class researchers, software engineers, and product teams to transform advanced research into scalable solutions for industries including autonomous vehicles, healthcare, robotics, cloud computing, cybersecurity, and accelerated computing.

Key Responsibilities

• Conduct research in machine learning, deep learning, statistical modeling, and artificial intelligence.
• Design, develop, and evaluate novel algorithms for predictive analytics and AI applications.
• Build and optimize large-scale machine learning models using structured and unstructured datasets.
• Research and improve Large Language Models (LLMs), Generative AI, and multimodal AI systems.
• Design experiments, analyze results, and present technical findings to research and engineering teams.
• Develop scalable data processing pipelines for model training and evaluation.
• Collaborate with software engineers to transition research prototypes into production-ready AI solutions.
• Publish research findings in leading AI and data science conferences and journals when appropriate.
• Stay current with emerging technologies and advancements in AI, machine learning, and data science.
• Mentor junior researchers and contribute to the organization's innovation initiatives.
• Optimize model performance, scalability, explainability, and efficiency.
• Ensure responsible AI practices, including fairness, transparency, privacy, and model governance.

Required Qualifications

• Master's or Ph.D. in Data Science, Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Mathematics, or a related quantitative field.
• 3–7+ years of experience in machine learning research, AI, or data science.
• Strong understanding of supervised, unsupervised, reinforcement learning, and deep learning techniques.
• Experience with Large Language Models (LLMs), transformer architectures, or generative AI is highly desirable.
• Proficiency in Python and common data science libraries.
• Experience working with large datasets and distributed computing environments.
• Strong analytical, problem-solving, and research skills.
• Excellent written and verbal communication skills.

Preferred Qualifications

• Publications in top AI conferences such as NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP, or KDD.
• Experience with distributed machine learning frameworks and GPU computing.
• Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
• Experience with Retrieval-Augmented Generation (RAG), vector databases, or AI agents.
• Knowledge of MLOps, model deployment, and scalable AI infrastructure.

Technical Skills

Programming Languages

• Python
• SQL
• C++
• Java
• R

AI & Machine Learning

• Machine Learning
• Deep Learning
• Generative AI
• Large Language Models (LLMs)
• Reinforcement Learning
• Transfer Learning
• Natural Language Processing (NLP)
• Computer Vision
• Time Series Forecasting

Frameworks & Libraries

• PyTorch
• TensorFlow
• JAX
• Scikit-learn
• XGBoost
• Hugging Face Transformers

Data Engineering & Big Data

• Apache Spark
• Apache Kafka
• Hadoop
• Delta Lake
• Databricks

Cloud & MLOps

• AWS
• Microsoft Azure
• Google Cloud Platform
• Docker
• Kubernetes
• MLflow
• Kubeflow

Databases

• PostgreSQL
• Snowflake
• BigQuery
• MongoDB
• Vector Databases (Pinecone, Weaviate, FAISS)

Visualization

• Tableau
• Power BI
• Matplotlib
• Plotly

Soft Skills

• Research and Innovation
• Critical Thinking
• Statistical Analysis
• Problem Solving
• Collaboration
• Technical Communication
• Leadership
• Project Management
• Adaptability
• Continuous Learning

Benefits

• Competitive Salary
• Annual Performance Bonus
• Restricted Stock Units (RSUs)
• Medical, Dental, and Vision Insurance
• Paid Time Off (PTO) and Paid Holidays
• Employee Stock Purchase Plan (ESPP)
• Professional Development and Conference Sponsorship
• Tuition Reimbursement
• Flexible Hybrid Work Environment
• Wellness Programs
• Employee Assistance Program (EAP)

Job Summary

We are seeking a highly skilled OT (Operational Technology) Cybersecurity Engineer to protect and secure industrial control systems (ICS), SCADA environments, manufacturing networks, and other critical operational technology infrastructure. The ideal candidate will have expertise in industrial cybersecurity, network security, risk management, and incident response while ensuring compliance with industry standards and regulatory requirements.

In this role, you will collaborate with engineering, IT, and plant operations teams to identify security risks, implement protective controls, monitor industrial environments, and respond to cyber threats affecting operational technology systems. Your work will play a critical role in maintaining the reliability, safety, and resilience of mission-critical industrial operations.

Key Responsibilities

• Design, implement, and maintain cybersecurity controls for Operational Technology (OT) environments.
• Secure Industrial Control Systems (ICS), SCADA systems, Distributed Control Systems (DCS), and PLC-based industrial networks.
• Conduct OT cybersecurity risk assessments and vulnerability assessments across manufacturing and industrial environments.
• Develop and implement security policies, procedures, and best practices for OT infrastructure.
• Monitor OT environments using security monitoring tools and SIEM platforms to detect malicious activity.
• Investigate and respond to cybersecurity incidents affecting industrial systems and critical infrastructure.
• Perform threat hunting and identify Indicators of Compromise (IOCs) within OT environments.
• Implement network segmentation strategies between IT and OT environments.
• Manage firewall configurations, industrial network security appliances, and secure remote access solutions.
• Collaborate with plant engineers, automation teams, and IT administrators to ensure secure system integration.
• Support secure deployment of industrial IoT (IIoT) devices and connected operational assets.
• Conduct security audits and compliance assessments for industrial facilities.
• Develop disaster recovery and incident response plans specific to OT environments.
• Perform security testing and validate remediation efforts for identified vulnerabilities.
• Maintain asset inventories for industrial devices, controllers, servers, and network equipment.
• Ensure compliance with cybersecurity standards such as NIST Cybersecurity Framework (CSF), IEC 62443, NERC CIP, and ISO/IEC 27001.
• Participate in security awareness initiatives for engineering and operations personnel.
• Document security architecture, technical procedures, and incident reports.
• Stay current with emerging OT cyber threats, attack techniques, and defensive technologies.

Required Qualifications

• Bachelor's degree in Cybersecurity, Computer Science, Information Technology, Electrical Engineering, Industrial Engineering, or a related field.
• 5+ years of experience in cybersecurity with at least 3 years focused on Operational Technology (OT) or Industrial Control Systems (ICS).
• Strong understanding of industrial automation and control systems.
• Experience securing SCADA, PLC, DCS, and HMI environments.
• Knowledge of industrial communication protocols including Modbus, DNP3, OPC UA, BACnet, Profinet, and EtherNet/IP.
• Experience with SIEM platforms, endpoint security solutions, IDS/IPS, and industrial security monitoring tools.
• Familiarity with network segmentation, Zero Trust principles, VPNs, and secure remote access technologies.
• Experience conducting vulnerability assessments and security audits in industrial environments.
• Strong understanding of cybersecurity frameworks such as NIST CSF, IEC 62443, MITRE ATT&CK for ICS, and CIS Controls.
• Excellent analytical, troubleshooting, and incident response skills.
• Strong communication and collaboration abilities.

Preferred Qualifications

• CISSP (Certified Information Systems Security Professional)
• GICSP (Global Industrial Cyber Security Professional)
• GRID (GIAC Response and Industrial Defense)
• GCIA (GIAC Certified Intrusion Analyst)
• CompTIA Security+
• ISA/IEC 62443 Cybersecurity Certificate
• Microsoft Azure Security Engineer or AWS Security Specialty certification (preferred)
• Experience working in manufacturing, energy, utilities, oil & gas, transportation, or critical infrastructure industries.

Technical Skills

• Industrial Control Systems (ICS)
• SCADA Security
• PLC Security
• DCS Architecture
• Industrial IoT (IIoT)
• Network Security
• Firewalls
• VPN
• Zero Trust Architecture
• SIEM Platforms (Splunk, Microsoft Sentinel, QRadar)
• Endpoint Detection & Response (EDR)
• Vulnerability Management
• Threat Hunting
• Incident Response
• Digital Forensics
• Network Segmentation
• Active Directory
• Windows Server
• Linux
• Python
• PowerShell
• Wireshark
• Nessus
• Nmap

Soft Skills

• Critical Thinking
• Problem Solving
• Communication Skills
• Team Collaboration
• Leadership
• Project Management
• Risk Assessment
• Attention to Detail
• Decision Making
• Adaptability

Benefits

• Competitive Salary
• Performance Bonus
• Medical, Dental, and Vision Insurance
• Paid Time Off (PTO)
• Paid Holidays
• Flexible Work Options
• Professional Certification Reimbursement
• Learning & Development Programs
• Employee Assistance Program (EAP)
• Career Growth Opportunities
• Wellness Programs

Job Description

We are seeking a highly analytical and results-driven Decision Scientist to join our Data Science team. In this role, you will leverage data, statistical analysis, machine learning, and business intelligence to drive strategic decision-making across the organization. You will partner with cross-functional teams to identify business opportunities, optimize operational performance, and deliver actionable insights through advanced analytics and predictive modeling.

The ideal candidate has a strong background in data science, statistics, experimentation, and business strategy, with the ability to translate complex data into clear recommendations for stakeholders and executive leadership.

Key Responsibilities

• Analyze large, complex datasets to identify trends, patterns, and business opportunities.
• Develop predictive, forecasting, and optimization models to support strategic business decisions.
• Design, execute, and evaluate A/B tests and other experiments to measure business impact.
• Build statistical models to improve customer acquisition, retention, pricing, and operational efficiency.
• Collaborate with product managers, business leaders, engineering, and analytics teams to solve high-impact business problems.
• Develop dashboards, reports, and visualizations to communicate insights effectively.
• Monitor key business metrics and recommend data-driven improvements.
• Conduct root cause analysis to identify factors influencing business performance.
• Apply machine learning and advanced analytics techniques to improve decision-making processes.
• Translate business requirements into analytical solutions and actionable recommendations.
• Ensure data quality, integrity, and consistency across multiple data sources.
• Present analytical findings to technical and non-technical stakeholders, including senior leadership.
• Document methodologies, models, and analytical processes to support knowledge sharing and reproducibility.
• Stay current with emerging data science methodologies, analytical tools, and industry best practices.

Required Qualifications

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Operations Research, Business Analytics, or a related quantitative field.
• 2+ years of experience in Data Science, Decision Science, Business Analytics, or Advanced Analytics.
• Strong proficiency in Python, SQL, and statistical analysis.
• Experience with predictive modeling, regression analysis, classification, clustering, and forecasting.
• Knowledge of machine learning algorithms and model evaluation techniques.
• Experience with data visualization tools such as Tableau or Power BI.
• Strong understanding of experimental design, A/B testing, and statistical inference.
• Excellent analytical, problem-solving, and communication skills.
• Ability to explain complex analytical concepts to non-technical audiences.

Preferred Qualifications

• Master's degree in Data Science, Statistics, Business Analytics, Economics, or a related field.
• Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
• Knowledge of big data technologies such as Apache Spark or Databricks.
• Familiarity with machine learning deployment and MLOps concepts.
• Experience in customer analytics, marketing analytics, pricing optimization, supply chain analytics, or financial modeling.
• Experience with Generative AI, Large Language Models (LLMs), or AI-assisted analytics is a plus.

Technical Skills

Programming Languages

• Python
• SQL
• R (Preferred)

Data Science & Analytics

• Statistical Analysis
• Predictive Modeling
• Machine Learning
• Time Series Forecasting
• Optimization Techniques
• A/B Testing
• Experimental Design
• Regression Analysis
• Classification & Clustering

Libraries & Frameworks

• Pandas
• NumPy
• Scikit-learn
• Statsmodels
• XGBoost
• LightGBM

Data Visualization

• Tableau
• Power BI
• Matplotlib
• Plotly

Databases

• PostgreSQL
• MySQL
• Snowflake
• BigQuery

Cloud Platforms

• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)

Soft Skills

• Analytical and critical thinking.
• Business problem-solving mindset.
• Strong communication and presentation skills.
• Stakeholder management.
• Cross-functional collaboration.
• Attention to detail.
• Project management and organization.
• Continuous learning and adaptability.

Preferred Certifications

• Microsoft Certified: Azure Data Scientist Associate
• AWS Certified Machine Learning – Specialty
• IBM Data Science Professional Certificate
• SAS Certified Data Scientist

Job Description

We are seeking an innovative and highly skilled AI Engineer (Generative AI & Large Language Models) to join our growing AI Engineering team. In this role, you will design, develop, deploy, and optimize AI-powered applications using Large Language Models (LLMs), Generative AI, and modern machine learning frameworks. You will collaborate with data scientists, software engineers, product managers, and business stakeholders to build intelligent, scalable, and production-ready AI solutions that enhance customer experiences and drive business innovation.

The ideal candidate has hands-on experience with LLMs, prompt engineering, Retrieval-Augmented Generation (RAG), vector databases, cloud platforms, and modern AI development frameworks. You should be passionate about staying current with advancements in AI technologies while building secure, reliable, and scalable AI applications.

Key Responsibilities

• Design, develop, and deploy AI-powered applications using Large Language Models (LLMs) and Generative AI technologies.
• Build Retrieval-Augmented Generation (RAG) pipelines using vector databases and enterprise knowledge sources.
• Develop intelligent chatbots, AI assistants, document processing systems, and workflow automation solutions.
• Design effective prompts and prompt engineering strategies to improve AI model accuracy and reliability.
• Integrate foundation models through APIs and open-source frameworks into production applications.
• Fine-tune, evaluate, and optimize AI models for business-specific use cases where appropriate.
• Develop scalable AI microservices and RESTful APIs for enterprise applications.
• Build data preprocessing and embedding pipelines for text, documents, and structured data.
• Monitor AI application performance, latency, quality, and operational metrics.
• Implement AI safety, security, governance, and responsible AI best practices.
• Collaborate with Data Scientists, Machine Learning Engineers, and Software Engineers throughout the AI development lifecycle.
• Deploy AI solutions on cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
• Optimize infrastructure costs and inference performance for production AI workloads.
• Perform model evaluation, benchmarking, and continuous improvement using automated testing and feedback.
• Document AI architectures, technical designs, deployment procedures, and operational guidelines.
• Stay current with emerging AI technologies, research papers, frameworks, and industry trends.

Required Qualifications

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related technical field (or equivalent practical experience).
• 3+ years of experience in software engineering, machine learning, or AI application development.
• Strong proficiency in Python and modern software development practices.
• Experience developing applications using Large Language Models (LLMs) and Generative AI technologies.
• Hands-on experience with AI orchestration frameworks such as LangChain, LlamaIndex, or similar tools.
• Experience building Retrieval-Augmented Generation (RAG) solutions.
• Familiarity with vector databases such as Pinecone, Chroma, FAISS, Weaviate, or Milvus.
• Strong understanding of REST APIs, microservices, and distributed systems.
• Experience working with cloud platforms including AWS, Microsoft Azure, or Google Cloud.
• Strong knowledge of Git, Docker, CI/CD pipelines, and software deployment practices.
• Excellent analytical, communication, and problem-solving skills.

Preferred Qualifications

• Master's degree in Artificial Intelligence, Computer Science, Data Science, or a related field.
• Experience with transformer architectures and deep learning frameworks such as PyTorch or TensorFlow.
• Knowledge of MLOps practices, model deployment, and AI lifecycle management.
• Experience with Kubernetes and container orchestration.
• Familiarity with SQL, NoSQL databases, and data engineering concepts.
• Understanding of AI governance, security, privacy, and compliance requirements.
• Experience deploying enterprise-scale AI solutions in production.
• Contributions to open-source AI projects or published AI research are a plus.

Technical Skills

Programming Languages

• Python
• SQL
• JavaScript (preferred)
• TypeScript (preferred)

AI & Machine Learning

• Large Language Models (LLMs)
• Generative AI
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• Fine-Tuning
• Embeddings
• AI Agents
• Model Evaluation
• Natural Language Processing (NLP)

Frameworks & Libraries

• LangChain
• LlamaIndex
• Hugging Face Transformers
• PyTorch
• TensorFlow
• Scikit-learn
• FastAPI
• Flask

Vector Databases

• Pinecone
• Chroma
• FAISS
• Weaviate
• Milvus

Cloud Platforms

• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)

DevOps & MLOps

• Docker
• Kubernetes
• Git
• GitHub Actions
• MLflow
• CI/CD Pipelines

Databases

• PostgreSQL
• MongoDB
• Redis

Soft Skills

• Strong analytical and critical thinking abilities.
• Excellent problem-solving skills.
• Effective verbal and written communication.
• Ability to collaborate in cross-functional teams.
• Strong organizational and time-management skills.
• Adaptability in a fast-paced, evolving technology environment.
• Passion for continuous learning and innovation.

Preferred Certifications

• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate
• Databricks Certified Machine Learning Professional
• TensorFlow Developer Certificate

Job Description

We are seeking a highly motivated Threat Intelligence Analyst to join our Cybersecurity team. In this role, you will identify, analyze, and monitor emerging cyber threats targeting our organization. You will collect and evaluate threat intelligence from multiple sources, track threat actors and attack techniques, and provide actionable insights to strengthen our security posture. The ideal candidate has strong analytical skills, experience with threat intelligence platforms, and a passion for staying ahead of evolving cyber threats.

Key Responsibilities

• Research, collect, and analyze cyber threat intelligence from internal and external sources.
• Monitor emerging threats, malware campaigns, ransomware groups, and nation-state activities.
• Identify Indicators of Compromise (IOCs), Tactics, Techniques, and Procedures (TTPs), and attack trends.
• Produce actionable threat intelligence reports and risk assessments for security teams and leadership.
• Collaborate with Security Operations Center (SOC), Incident Response, and Vulnerability Management teams to improve threat detection and response.
• Conduct proactive threat hunting using intelligence-driven methodologies.
• Utilize frameworks such as MITRE ATT&CK to map adversary behaviors and identify defensive gaps.
• Monitor dark web forums, threat feeds, and open-source intelligence (OSINT) for relevant threats.
• Develop and maintain threat intelligence dashboards, reports, and executive briefings.
• Recommend security improvements based on intelligence findings and emerging risks.
• Support incident investigations by providing contextual threat intelligence.
• Stay current with the latest cybersecurity trends, threat actors, attack techniques, and industry best practices.

Required Qualifications

• Bachelor's degree in Cybersecurity, Computer Science, Information Technology, or a related field (or equivalent experience).
• 2+ years of experience in Cybersecurity, Threat Intelligence, SOC, or Incident Response.
• Strong understanding of network security, malware analysis, and cyber attack methodologies.
• Experience with SIEM platforms such as Splunk, Microsoft Sentinel, or QRadar.
• Familiarity with threat intelligence platforms (TIPs), OSINT tools, and malware analysis tools.
• Knowledge of MITRE ATT&CK, Cyber Kill Chain, and common threat frameworks.
• Excellent analytical, problem-solving, and communication skills.
• Ability to work independently and collaboratively in a fast-paced environment.

Preferred Qualifications

• Experience with Python, PowerShell, or other scripting languages.
• Knowledge of cloud security (AWS, Azure, or Google Cloud).
• Familiarity with threat hunting, digital forensics, and incident response.
• Experience using SOAR platforms and security automation tools.
• Industry certifications such as CompTIA Security+, CySA+, GCIH, GCIA, GCFA, CISSP, or Certified Threat Intelligence Analyst (CTIA) are a plus.

Key Skills

• Threat Intelligence Analysis
• Threat Hunting
• Malware Analysis
• Threat Actor Tracking
• SIEM & Log Analysis
• Incident Response
• MITRE ATT&CK Framework
• OSINT Research
• Risk Assessment
• Digital Forensics
• Network Security
• Python/PowerShell
• Cloud Security
• Communication & Reporting