Senior Consultant, AI/ML Engineering
AstraZeneca (company site, opens in a new tab)6+ yrsBengaluruOn-siteDirect career pageEst. 30–45 LPA
Posted 7h ago
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Job description
Structured overview of role & requirements
About This Role
- Own end-to-end delivery of Generative AI and agentic solutions for commercial use cases, from problem framing through deployment.
- Build evaluation, safety, telemetry and monitoring capabilities; improve production systems for quality, reliability, cost and latency.
- Deliver classical ML and data-integrated solutions, lead technical workstreams, and set production code standards while coaching junior colleagues.
Minimum Requirements
- Work Experience Required: Typically 6+ years building data science/ML solutions, including typically 1+ year of recent hands-on LLM application experience; must have independently led AI or data science projects.
- Education: BS or equivalent experience in a quantitative field such as computer science, mathematics, statistics, engineering, physics or computational sciences.
- Technical requirements: Strong Python; SQL and NoSQL familiarity; classical ML and deep learning (including transformers) using PyTorch or TensorFlow; LLM prompt/context engineering, RAG, fine-tuning/distillation knowledge, agent or multi-agent workflow development, and LLM/agent evaluation; working knowledge of AWS.
- Location/onsite: Bangalore; office attendance averages at least three days per week.
Ideal Candidate Profile
- Has hands-on experience taking LLM and agentic systems into production, including evaluation and operational monitoring—not only experimentation.
- Can independently lead applied AI work across commercial problems and integrate structured and unstructured data with platform and data engineering partners.
- Pharma, healthcare or commercial analytics experience is a plus; reinforcement learning, AI observability and MLOps experience can strengthen the fit.