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)