Senior Principal Machine Learning Engineer
Eli Lilly and CompanyMatch Score
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Protocol Intelligence
Data-driven signals on your job's competitivenessHighly specialized senior ML/GenAI role with principal-level experience requirement reduces candidate density.
Requires deep GenAI and MLOps expertise, moderately transferable but favors specialized candidates.
Explicit 11–15 years requirement, principal-level ML/MLOps ownership, and mandatory tech stack make shortlisting stringent.
Job Description
Structured overview of role & requirementsAbout This Role
Design and build production backend systems for agentic AI applications including API layers, session/state management, and streaming for concurrent users.
Lead resolution of complex, cross-system technical challenges and set technical standards for engineering and MLOps practices across multiple teams.
Own GitOps, CI/CD pipelines, platform reliability, architecture for AI systems, and mentor engineers on design and production practices.
Minimum Requirements
11–15 years of hands-on experience with architecture-level ownership across multiple teams or systems.
Strong proficiency in Python and experience with containerisation (Docker), orchestration (Kubernetes), and CI/CD pipelines.
Experience developing or deploying LLM-based applications including prompt engineering, RAG, or agentic workflows.
Bachelor's or Master's degree in Computer Science, Computer Applications, or related technical field.
Ideal Candidate Profile
Recognized expert with cross-functional influence capable of making key technical decisions impacting multiple teams.
Experienced in MLOps, platform reliability, and advanced AI system architectures including GenAI and agent frameworks.
Proficient operating in Agile/Scrum environments with knowledge of AWS cloud services and enterprise data platforms (e.g. Databricks).