Staff AI/ML Engineer, Applied AI

Overview

Staff AI/ML Engineer, Applied AI, providing hands-on technical leadership across the AI/ML lifecycle—from research and experimentation to production deployment of AI/ML and GenAI solutions.

What you'll do

• Lead end-to-end AI/ML lifecycle activities including data engineering, model development, evaluation, and deployment.
• Architect and build machine learning/deep learning models, LLM applications, RAG solutions, and agentic workflows.
• Develop and deploy LLM-powered services using Azure OpenAI, Anthropic Claude, and OpenAI-compatible APIs.
• Implement agentic AI and RAG workflows including ingestion, chunking, embeddings, vector search, tool calling, and prompt engineering.
• Build GenAI systems using LangChain and LangGraph for orchestration and workflow integration.
• Mentor engineers and influence AI/Generative AI engineering standards and evaluation frameworks.

What you'll need

• Master’s degree in AI/ML, computer science, statistics, engineering, or a related technical field.
• 10+ years of industry experience in software engineering and developing AI/ML solutions shipped into production.
• 5+ years of experience working in agile/scrum environments.
• Hands-on experience deploying deep learning/ML methods into real production systems.
• Strong proficiency in Python and PyTorch, and also C++ and C#.
• Strong data engineering skills using ETL/data pipelines and tools such as Pandas and NumPy.
• Experience building production-grade RAG and agentic AI solutions.

Nice to have

• Hands-on experience applying AI/ML in life sciences, genomics, materials sciences, healthcare, or regulatory settings.
• Experience with MLOps or LLMOps concepts including deployment, monitoring, and observability.
• Experience applying AI/ML to computational biology.
• Experience with cloud platforms such as Azure, AWS, or GCP.

Details

• Location: Bangalore, India.