Lilly
Healthcare
Engineer-MLOps&ScientificPlatforms-DataFoundry
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Engineer - MLOps & Scientific Platforms - Data Foundry at Lilly. Skills: MLOps, Scientific Platforms, Data Foundry, AI/ML. Build ML deployment pipelines. Maintain ML deployment pipelines”
Industry & Context.
Root cause analysis; Debugging; Performance optimization; Troubleshooting
What They're Looking For.
Must Have
B.S. or M.S. in Computer Science, 3+ years MLOps experience, 3+ years ML engineering experience, 3+ years scientific platform development experience, Authorized to work in US full-time
Nice to Have
Pharmaceutical or biotech research experience, Python experience with ML frameworks, ML lifecycle tools experience, Production model serving infrastructure experience, Containerization experience, API gateway patterns familiarity, Event-driven architectures familiarity, Service mesh technologies familiarity, Feature stores experience, Data versioning experience, Experiment tracking at scale experience, AI agent frameworks exposure, APIs AI systems invoke exposure, C experience, C++ experience, CUDA experience, GPU-accelerated computing experience, Containerizing HPC workloads experience, Singularity/Apptainer experience
What You'll Do.
Build ML deployment pipelines
Maintain ML deployment pipelines
Serve containerized models
Set retraining triggers
Develop model registry infrastructure
Enable computational scientists access
Implement monitoring for data pipelines
Implement alerting for data pipelines
Implement monitoring for APIs
Implement alerting for APIs
Implement monitoring for ML models
Implement alerting for ML models
Implement monitoring for agentic systems
Implement alerting for agentic systems
Build dashboards for pipeline execution
Build metrics for pipeline execution
Build dashboards for API latency
Build metrics for API latency
Build dashboards for token usage
Build metrics for token usage
Build dashboards for model prediction quality
Build metrics for model prediction quality
Build dashboards for system health
Build metrics for system health
Establish structured logging
Establish tracing infrastructure
Deploy predictive methods
Deploy analytical methods
Ensure versioning for methods
Ensure error handling for methods
Ensure response-time guarantees for methods
Enable insight generation
Productionize methods
Build serving infrastructure for synchronous workloads
Build serving infrastructure for asynchronous workloads
Implement API contracts
Define documentation standards
Implement documentation standards
Define testing frameworks
Implement testing frameworks
Build cloud-native model serving infrastructure
Operate cloud-native model serving infrastructure
Use containers for infrastructure
Use Kubernetes for infrastructure
Use infrastructure-as-code
Develop CI/CD pipelines for ML models
Automate ML model validation
Perform A/B testing for ML models
Implement canary deployments for ML models
Implement rollback procedures for ML models
Integrate model serving with data pipelines
Ensure models access training data
Ensure models access inference data
Partner to expose scientific tools via interfaces
Collaborate on API performance requirements
Ensure deployed models include uncertainty quantification
Ensure deployed models include confidence metrics
How You'll Work.
Team & Collaboration
Frontier AI team; Tech@Lilly; Methods4Insight scientists
Communication Scope
API documentation
Full Job Description
At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world. **Locations:** San Diego, CA; San Francisco, CA; Boston, MA; Louisville, CO; Indianapolis, IN **Lilly Small Molecule Discovery** is purpose-built to create molecules that make life better for people. **Discovery Technology and Platforms (DTP)** accelerates molecule discovery by building optimized foundational platforms, streamlining lab operations through advanced technologies and data connectivity, and investing in novel capabilities. **Data Foundry** is a multidisciplinary team within DTP that enables AI-native drug discovery through four integrated pillars: **Architecture4Insight** (data infrastructure and scientific software), **Methods4Insight** (analytical and computational methods), **Automation & Scale4Insight** (lab automation and agentic workflows), and **Preparedness4Insight** (data governance and readiness). These pillars empower every Lilly scientist to make optimal decisions by providing seamless access to data, insights, and AI-driven capabilities—serving both human scientists and autonomous AI agents. # **Position Summary** We are seeking an **Engineer - MLOps & Scientific Platforms - Data Foundry** to operationalize Data Foundry’s scientific tools and analytical methods into actionable-prototypes. You will build the ML deployment pipelines, model serving infrastructure, API layers, and observability guardrails that make our scientific discovery methods and tools reliable, scalable, and consumable, both by disc
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