Applied AI And Machine Learning Scientist

Job Summary

We are seeking an experienced Applied AI & Machine Learning Scientist to develop and deploy cutting-edge artificial intelligence and machine learning solutions that solve complex business and engineering challenges. In this role, you will research, build, and optimize predictive models, deep learning systems, and Generative AI applications while collaborating with software engineers, data scientists, and product teams. The ideal candidate is passionate about AI innovation and has hands-on experience delivering production-ready machine learning solutions at scale.

Key Responsibilities

• Design, develop, and deploy machine learning and deep learning models for production environments.
• Build AI-powered applications using supervised, unsupervised, and reinforcement learning techniques.
• Develop and optimize Large Language Model (LLM) and Generative AI solutions.
• Perform data preprocessing, feature engineering, and exploratory data analysis.
• Train, evaluate, and fine-tune machine learning models to improve performance and accuracy.
• Collaborate with Data Engineers and MLOps teams to build scalable AI pipelines.
• Deploy AI models using cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
• Monitor model performance and implement continuous improvements.
• Conduct research on emerging AI technologies and evaluate their business applications.
• Develop recommendation systems, predictive analytics, computer vision, or natural language processing (NLP) solutions.
• Document AI models, experiments, and technical processes.
• Follow Responsible AI, data privacy, and model governance best practices.

Required Qualifications

• Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, or a related field (Bachelor’s degree with equivalent industry experience may also be considered).
• 4–8+ years of experience in Machine Learning, Artificial Intelligence, or Data Science.
• Strong programming skills in Python and SQL.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, or XGBoost.
• Strong understanding of statistics, probability, optimization, and predictive modeling.
• Experience deploying machine learning models into production environments.
• Familiarity with cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience with Large Language Models (LLMs) and Generative AI technologies.
• Hands-on experience with Retrieval-Augmented Generation (RAG), vector databases, and prompt engineering.
• Experience with NLP, computer vision, recommendation systems, or time-series forecasting.
• Knowledge of MLOps tools such as MLflow, Kubeflow, SageMaker, or Vertex AI.
• Experience with distributed computing frameworks such as Apache Spark or Ray.
• Publications or contributions to AI research or open-source machine learning projects are a plus.

Technical Skills

• Programming: Python, SQL, R
• Machine Learning: Scikit-learn, XGBoost, LightGBM
• Deep Learning: TensorFlow, PyTorch, Keras
• Generative AI: OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex
• Large Language Models: GPT, Llama, Mistral, Gemini
• Data Processing: Pandas, NumPy, Apache Spark
• Cloud Platforms: AWS, Microsoft Azure, Google Cloud Platform (GCP)
• MLOps: MLflow, Kubeflow, Docker, Kubernetes
• Visualization: Tableau, Power BI, Matplotlib
• Version Control: Git, GitHub

Preferred Certifications

• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate (AI-102)
• Google Professional Machine Learning Engineer
• Databricks Certified Machine Learning Professional
• TensorFlow Developer Certificate

Benefits

• Competitive salary with annual performance bonuses
• Medical, dental, and vision insurance
• Paid vacation, holidays, and parental leave
• Hybrid work flexibility
• Learning and certification reimbursement
• Access to advanced AI research and high-performance computing resources
• Career growth opportunities in AI, machine learning, and data science