Machine Learning Engineer
Eli Lilly and CompanyMatch Score
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Job Description
Structured overview of role & requirementsAbout This Role
Build and maintain production-grade machine learning and AI components and services, owning small features or workstreams end-to-end from design through deployment.
Develop and manage CI/CD pipelines and deploy ML/AI workloads using Docker, Kubernetes, Prefect, and cloud platforms like AWS.
Support model deployment lifecycle including monitoring, retraining, and resolving production issues across multiple system components.
Minimum Requirements
0–4 years of hands-on experience building and operating ML/AI systems in production.
Proficiency in Python with ability to write clean, testable, production-quality code.
Experience with containerisation (Docker), orchestration (Kubernetes), and CI/CD pipelines (e.g., GitHub Actions).
Bachelor's or Master's degree in Computer Science, Computer Applications, or related technical field.
Ideal Candidate Profile
Experienced with Agile/Scrum environments and software engineering best practices including version control, testing, and code reviews.
Familiarity with AWS cloud services and enterprise data platforms such as Databricks and Unity Catalog.
Capable of independently taking ownership of ML/AI features end-to-end including deployment, debugging, and monitoring in production systems.