Engineer - MLOps & Scientific Platforms - Data Foundry
$66,000–$165,000 year
On-site · San Francisco, California, United States or Boston, Massachusetts, United States
Job Summary
Engineer to operationalize Data Foundry’s scientific tools and analytical methods into actionable-prototypes. Build end-to-end ML deployment pipelines, model serving infrastructure, API layers, and observability guardrails to ensure reliability and scalability for both discovery scientists and autonomous agents. Collaborate across Methods4Insight and Architecture4Insight to ensure tools are analytics-ready, well-monitored, and exposed via APIs with response-time guarantees. Deploy predictive methods (cheminformatics, structural biology, bioinformatics, reaction informatics) with versioning, error handling, and performance guarantees. Develop cloud-native infrastructure (AWS/Azure/GCP), CI/CD for ML models, and API contracts; partner with Frontier AI and Tech@Lilly. Establish monitoring, logging, and dashboards; optimize data pipelines, API latency, token usage, and model quality. Ensure uncertainty quantification and robust integration of scientific tools with external teams including Frontier AI.
Required Qualifications
- B.S. or M.S. in Computer Science, Data Science, Machine Learning, Bioinformatics, Computational Biology, or related field
- 3+ years of experience in MLOps, ML engineering, or scientific platform development
- Authorized to work in the United States on a full-time basis
- Lilly will not provide sponsorship for work authorization or visas
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