ML Ops Engineer: Scale Production AI Platforms

BioSpace; San Francisco (CA); Hybrid; USD 147,000 - 268,000; Full time

Benefits offered by this job

Bonus program

401(k)

Medical/Dental/Vision

Job summary

Lilly is seeking an experienced ML Ops Engineer for its Silicon Valley AI co-innovation lab. You will build and operate platforms enabling end-to-end ML lifecycle, from deployment to monitoring, with a focus on scalable infrastructure for cutting-edge drug discovery applications.

You will collaborate with data scientists and engineers to deploy production-ready AI capabilities, optimize GPU resources, and automate workflows using IaC and CI/CD practices in a hybrid work setting.

Qualifications

• Bachelor's degree in a technical field and 4+ years of ML engineering/ML Ops experience.
• Experience deploying and maintaining production ML platforms and models.

Responsibilities

• Lead deployment, monitoring, and reliability of ML models.
• Operate and optimize large-scale inference platforms for research and production.
• Ensure production readiness: deployment, scaling, monitoring, and maintenance.
• Test and improve model accuracy through systematic evaluation.
• Collaborate with data scientists, AI engineers, and infrastructure teams.
• Automate platform with IaC and CI/CD; document for operability.

Skills

Python

ML Ops

Collaboration

CI/CD

Education

Bachelor's degree in CS/Engineering/Math/Statistics

Tools

MLflow

Weights & Biases

KServe

Docker

Kubernetes

Terraform

GitHub Actions

Job description

Lilly is seeking an experienced ML Ops Engineer for its Silicon Valley AI co-innovation lab. You will build and operate platforms enabling end-to-end ML lifecycle, from deployment to monitoring, with a focus on scalable infrastructure for cutting-edge drug discovery applications.

You will collaborate with data scientists and engineers to deploy production-ready AI capabilities, optimize GPU resources, and automate workflows using IaC and CI/CD practices in a hybrid work setting.