Principal Machine Learning Engineer

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.

Overview We are looking for a Principal Machine Learning Engineer to join the AI Engineering team, with a primary focus on Hands-On Engineering (MLE) and MLOps & Platform Reliability and GenAI & Agentic Systems. This posting is at level R3 on our engineering ladder — see the level framing below for the expected scope of ownership and impact. Level framing: Recognized technical expert; leads decisions on technical approach for projects; solves complex problems and innovates solutions; drives improvements across multiple projects/teams; may manage budgets.

Design and build complex ML/AI systems and services, setting the technical approach for your workstream. Solve complex, ambiguous technical problems that span multiple components or teams. Set code-quality and engineering standards for your area, and lead by example in code review. Own the MLOps design for a significant system: CI/CD, orchestration (Kubernetes/Prefect), and production monitoring. Lead root-cause analysis for complex production incidents and drive systemic fixes, not just patches. Extend the team's 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 for your area: evaluation pipelines, guardrails, and cost/latency optimization. Evaluate and introduce new GenAI tools, frameworks, or techniques where they meaningfully improve the platform. Mentor other engineers and help raise technical standards within your workstream. Key Tools & Technologies Cloud & Data Infra: AWS (EC2/ECS, S3, Lambda, IAM, CloudWatch or equivalent); Databricks & Unity Catalog Foundational: Python; Git/GitHub; software engineering best practices; testing; SQL MLOps & Deployment: Docker, Kubernetes, Prefect; CI/CD (GitHub Actions); production monitoring; model versioning & lineage; GitOps governance GenAI & Agentic Architecture: Claude or comparable LLMs; LangGraph or comparable agent frameworks; RAG architectures; vector databases (e.g. Pinecone); prompt engineering & evaluation Required Qualifications 8–11 years of hands-on experience, with a track record of owning significant technical workstreams end-to-end. Strong proficiency in Python and a track record of writing 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, including prompt engineering, RAG, or agentic workflows. Strong working knowledge of containerisation (Docker), orchestration (Kubernetes), and CI/CD pipelines. Working knowledge of AWS cloud services and Databricks/Unity Catalog or equivalent enterprise data platforms. Excellent verbal and written communication skills. Experience working in Agile/Scrum environments.

Bachelor's or Master's degree in Computer Science, Computer Applications, or a related technical field. Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (