Overview
Lead AI/ML Engineer for Applied AI, providing hands-on technical leadership across the AI/ML lifecycle and production deployment of AI/ML and Generative AI solutions.
What you'll do
- Lead AI/ML lifecycle activities from ideation and research through evaluation, performance tuning, and deployment.
- Architect and build machine learning/deep learning models, LLM applications, and RAG solutions.
- Develop and deploy agentic AI workflows including data ingestion, embeddings, vector search, retrieval, and prompt engineering.
- Build LLM-powered services using Azure OpenAI, Anthropic Claude, and OpenAI-compatible APIs.
- Integrate Generative AI capabilities into enterprise platforms and scientific/end-to-end workflows.
- Establish evaluation-driven practices and promote consistent adoption across the organization.
- Mentor engineers and progressively lead a team as headcount grows.
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 real production systems.
- 5+ years of experience working in agile/scrum environments.
- 2+ years of experience leading, supervising, and developing technical talent in an applied AI/ML setting.
- Hands-on experience deploying deep learning and related approaches into production systems.
- Strong proficiency in Python, PyTorch, C++, C#, and other relevant programming languages/frameworks.
- Experience with production-grade RAG and agentic AI solutions using embeddings, retrieval, tool calling, orchestration, and evaluation.
Nice to have
- Preferred Ph.D. degree.
- Preferred experience deploying AI/ML models for life sciences, genomics, materials sciences, healthcare, or other regulatory settings.
- Preferred MLOps or LLMOps concepts (deployment, monitoring, orchestration, observability, model lifecycle management).
- Preferred experience applying AI/ML methods to computational biology.
- Preferred experience with cloud platforms such as Azure, AWS, or GCP.
Details
- Location: Bangalore, India.
- Work schedule: Mon-Fri.
Read the full description and apply on the company’s own careers page.
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