Principal Machine Learning Engineer

Overview

Principal Machine Learning Engineer for Eli Lilly’s AI Engineering team, focused on hands-on MLE, MLOps/platform reliability, and GenAI/agentic systems.

What you'll do

• Design and build complex ML/AI systems and services, setting technical approach for your workstream.
• Lead MLOps design for a significant system, including CI/CD, orchestration (Kubernetes/Prefect), and production monitoring.
• Lead root-cause analysis for complex production incidents and drive systemic fixes.
• Extend MLOps frameworks to support new model types or deployment patterns.
• Lead design of agentic AI systems (e.g., LangGraph-based), including multi-step reasoning and RAG architecture decisions.
• Own LLMOps practices such as evaluation pipelines, guardrails, and cost/latency optimization.

What you'll need

• 8–11 years of hands-on experience owning significant technical workstreams end-to-end.
• Strong proficiency in Python and a track record of clean, testable, production-quality code.
• Demonstrated experience owning CI/CD, containerisation, and orchestration for production ML/AI systems.
• Proven experience developing or deploying LLM-based applications (prompt engineering, RAG, or agentic workflows).
• Strong working knowledge of Docker, Kubernetes, and CI/CD pipelines.
• Working knowledge of AWS cloud services and Databricks/Unity Catalog or equivalent enterprise data platforms.
• Bachelor’s or Master’s degree in Computer Science, Computer Applications, or a related technical field.

Details

• Location: Lilly Bengaluru (IN: Lilly Bengaluru).