✦ Luna Orbit — AI & Machine Learning

Engineer - MLOps & Scientific Platforms - Data Foundry

at Eli Lilly

📍 5 Locations Unknown Posted March 19, 2026
Type Not Specified
Experience mid
Exp. Years Not specified
Education Not specified
Category AI & Machine Learning

This role involves operationalizing AI and scientific tools within Lilly’s Data Foundry to enable AI-native drug discovery. The engineer will build deployment pipelines, APIs, and observability systems for scalable scientific AI applications.

  • Build ML deployment pipelines
  • Develop APIs for scientific tools
  • Ensure system observability
  • Operationalize AI models
  • Support scalable AI infrastructure

The position requires expertise in MLOps, ML deployment pipelines, API development, and data connectivity within a scientific research environment, focusing on AI-driven drug discovery platforms.

The ideal candidate is an experienced engineer with expertise in MLOps, machine learning deployment, and scientific data platforms. They should have a strong background in building scalable AI infrastructure for drug discovery and research environments.

MLOpsMachine LearningAPI developmentModel deploymentData connectivity
Data InfrastructureScientific SoftwareAI-native drug discoveryModel servingObservability
ML deployment pipelinesModel serving infrastructureAPIsObservability tools
MLOpsMachine LearningData InfrastructureScientific SoftwareAPI developmentModel deploymentModel servingObservabilityData connectivity
MLOpsMachine LearningData InfrastructureScientific SoftwareAPI developmentModel deploymentModel servingObservabilityData connectivityAI-native drug discovery
Problem-solvingCollaborationCommunicationAnalytical thinkingAdaptability
Industry Healthcare IT
Job Function Operationalize scientific AI tools and infrastructure for drug discovery
Role Subtype Data Scientist
Tech Domains Machine Learning, APIs, Data Infrastructure
MLOpsMachine LearningData InfrastructureScientific SoftwareAPI developmentModel deploymentModel servingObservabilityAI-native drug discoverydata connectivityML pipelinesAIscientific toolsscalable infrastructuremlopsmachine learningapi developmentmodel deploymentmodel servingscientific softwareai-nativedrug discoveryobservability

Lack of experience with MLOps or ML deployment, No background in scientific software or AI research, Familiarity only with general software engineering

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