{"schemaVersion":"jobsearcher.job.v1","id":"8ac9cef284da604789f39b79","url":"https://jobsearcher.com/jobs/8ac9cef284da604789f39b79","canonicalUrl":"https://jobsearcher.com/jobs/8ac9cef284da604789f39b79","title":"Engineer - MLOps & Scientific Platforms - Data Foundry","description":"Locations\nSan Diego, CA; San Francisco, CA; Boston, MA; Louisville, CO; Indianapolis, IN\n\nPosition Summary\nWe 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 discovery scientists and by the Frontier AI group’s autonomous agents.\n\nThis role sits at the interface between Methods4Insight (which develops analytical methods) and Architecture4Insight (which provides the agile data infrastructure). Your job is to ensure every scientific tool Data Foundry produces are analytics‑ready, well‑monitored, and exposed through APIs with the response‑time guarantees and error handling that both human users and AI agents require.\n\nResponsibilities\nMLOps & Model Lifecycle Management\n\nBuild and maintain end‑to‑end ML deployment pipelines: experiment tracking, model versioning (MLflow, Weights & Biases), containerized model serving, and automated retraining triggers.\n\nDevelop model registry infrastructure and feature engineering pipelines that enable computational scientists to access models.\n\nImplement monitoring and alerting for data pipelines, APIs, ML models, and agentic systems (LLMOps) to ensure system reliability and performance at scale.\n\nBuild dashboards and metrics tracking for pipeline execution, API latency, token usage, model prediction quality, and system health.\n\nEstablish structured logging and tracing infrastructure for debugging and performance optimization across scientific data systems.\n\nScientific Tool Agile Deployment\n\nDeploy predictive and analytical methods from Methods4Insight (cheminformatics, structural biology, bioinformatics, reaction informatics) with versioning, structured error handling, and response‑time guarantees that enable insight generation in an agile manner. Productionize when and where needed in partnership with Tech@Lilly.\n\nBuild serving infrastructure supporting both synchronous (interactive scientist queries) and asynchronous (batch and agent‑invoked) workloads in partnership with Tech@Lilly and Frontier AI.\n\nDefine and implement API contracts, documentation standards, and testing frameworks that ensure scientific tools are analysis ready, robust and consumable by external teams including Frontier AI.\n\nPlatform Engineering & Integration\n\nBuild and operate cloud‑native model serving infrastructure (AWS, Azure, or GCP) using containers, Kubernetes, and infrastructure‑as‑code.\n\nDevelop CI/CD pipelines for ML models: automated validation, A/B testing, canary deployments, and rollback procedures.\n\nIntegrate model serving with Data Foundry’s data pipelines, ensuring models have access to properly formatted, versioned training and inference data.\n\nFrontier AI Interface & Collaboration\n\nPartner with the Frontier AI team and Tech@Lilly to ensure Data Foundry’s scientific tools are exposed via well‑defined interfaces (REST APIs, MCP‑compatible endpoints) that agents can invoke programmatically.\n\nCollaborate on API performance requirements: latency targets, throughput guarantees, and graceful degradation under load.\n\nWork with Methods4Insight scientists to ensure deployed models include appropriate uncertainty quantification and confidence metrics.\n\nBasic Requirements\n\nB.S. or M.S. in Computer Science, Data Science, Machine Learning, Bioinformatics, Computational Biology, or related field.\n\n3+ years of experience in MLOps, ML engineering, or scientific platform development.\n\nQualified applicants must be authorized to work in the United States on a full‑time basis. Lilly will not provide support for or sponsor work authorization or visas for this role, including but not limited to F‑1 CPT, F‑1 OPT, F‑1 STEM OPT, J‑1, H‑1B, TN, O‑1, E‑3, H‑1B1, or L‑1.\n\nPreferred Qualifications\n\nPharmaceutical or biotech research industry experience.\n\nStrong Python skills; experience with ML frameworks (PyTorch, TensorFlow, scikit‑learn) and ML lifecycle tools (MLflow, W&B, Kubeflow, or similar).\n\nProven track record building and deploying production model serving infrastructure — containerized endpoints, RESTful/gRPC APIs, and operational monitoring.\n\nWorking knowledge of cloud platforms (AWS, Azure, or GCP), Kubernetes, and CI/CD automation.\n\nStrong communication skills with ability to collaborate across computational scientists, software engineers, and partner teams.\n\nExperience operationalizing scientific or computational models (cheminformatics, bioinformatics, structural biology, QSAR, molecular simulations, PK/PD, systems biology, or ODE‑based models).\n\nHands‑on experience with model monitoring, drift detection, and automated retraining systems.\n\nFamiliarity with API gateway patterns, event‑driven architectures, and service mesh technologies.\n\nExperience with feature stores, data versioning (DVC), or experiment tracking at scale.\n\nExposure to AI agent frameworks (MCP, LangChain) or building APIs that AI systems invoke programmatically.\n\nExperience with C, C++, CUDA, or GPU‑accelerated computing for optimizing model training/inference performance; familiarity with containerizing HPC workloads (Singularity/Apptainer).\n\nLilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.\n\nLilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.\n\nActual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is $66,000 - $165,000. Full‑time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company‑sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well‑being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities). Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.\n\n#J-18808-Ljbffr","company":"Initial Therapeutics","rawCompany":"initial therapeutics","city":"Millbrae","state":"CA","isRemote":false,"isActive":true,"createdAt":"2026-06-17T03:38:22.833Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Engineer - MLOps & Scientific Platforms - Data Foundry","description":"Locations\nSan Diego, CA; San Francisco, CA; Boston, MA; Louisville, CO; Indianapolis, IN\n\nPosition Summary\nWe 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 discovery scientists and by the Frontier AI group’s autonomous agents.\n\nThis role sits at the interface between Methods4Insight (which develops analytical methods) and Architecture4Insight (which provides the agile data infrastructure). Your job is to ensure every scientific tool Data Foundry produces are analytics‑ready, well‑monitored, and exposed through APIs with the response‑time guarantees and error handling that both human users and AI agents require.\n\nResponsibilities\nMLOps & Model Lifecycle Management\n\nBuild and maintain end‑to‑end ML deployment pipelines: experiment tracking, model versioning (MLflow, Weights & Biases), containerized model serving, and automated retraining triggers.\n\nDevelop model registry infrastructure and feature engineering pipelines that enable computational scientists to access models.\n\nImplement monitoring and alerting for data pipelines, APIs, ML models, and agentic systems (LLMOps) to ensure system reliability and performance at scale.\n\nBuild dashboards and metrics tracking for pipeline execution, API latency, token usage, model prediction quality, and system health.\n\nEstablish structured logging and tracing infrastructure for debugging and performance optimization across scientific data systems.\n\nScientific Tool Agile Deployment\n\nDeploy predictive and analytical methods from Methods4Insight (cheminformatics, structural biology, bioinformatics, reaction informatics) with versioning, structured error handling, and response‑time guarantees that enable insight generation in an agile manner. Productionize when and where needed in partnership with Tech@Lilly.\n\nBuild serving infrastructure supporting both synchronous (interactive scientist queries) and asynchronous (batch and agent‑invoked) workloads in partnership with Tech@Lilly and Frontier AI.\n\nDefine and implement API contracts, documentation standards, and testing frameworks that ensure scientific tools are analysis ready, robust and consumable by external teams including Frontier AI.\n\nPlatform Engineering & Integration\n\nBuild and operate cloud‑native model serving infrastructure (AWS, Azure, or GCP) using containers, Kubernetes, and infrastructure‑as‑code.\n\nDevelop CI/CD pipelines for ML models: automated validation, A/B testing, canary deployments, and rollback procedures.\n\nIntegrate model serving with Data Foundry’s data pipelines, ensuring models have access to properly formatted, versioned training and inference data.\n\nFrontier AI Interface & Collaboration\n\nPartner with the Frontier AI team and Tech@Lilly to ensure Data Foundry’s scientific tools are exposed via well‑defined interfaces (REST APIs, MCP‑compatible endpoints) that agents can invoke programmatically.\n\nCollaborate on API performance requirements: latency targets, throughput guarantees, and graceful degradation under load.\n\nWork with Methods4Insight scientists to ensure deployed models include appropriate uncertainty quantification and confidence metrics.\n\nBasic Requirements\n\nB.S. or M.S. in Computer Science, Data Science, Machine Learning, Bioinformatics, Computational Biology, or related field.\n\n3+ years of experience in MLOps, ML engineering, or scientific platform development.\n\nQualified applicants must be authorized to work in the United States on a full‑time basis. Lilly will not provide support for or sponsor work authorization or visas for this role, including but not limited to F‑1 CPT, F‑1 OPT, F‑1 STEM OPT, J‑1, H‑1B, TN, O‑1, E‑3, H‑1B1, or L‑1.\n\nPreferred Qualifications\n\nPharmaceutical or biotech research industry experience.\n\nStrong Python skills; experience with ML frameworks (PyTorch, TensorFlow, scikit‑learn) and ML lifecycle tools (MLflow, W&B, Kubeflow, or similar).\n\nProven track record building and deploying production model serving infrastructure — containerized endpoints, RESTful/gRPC APIs, and operational monitoring.\n\nWorking knowledge of cloud platforms (AWS, Azure, or GCP), Kubernetes, and CI/CD automation.\n\nStrong communication skills with ability to collaborate across computational scientists, software engineers, and partner teams.\n\nExperience operationalizing scientific or computational models (cheminformatics, bioinformatics, structural biology, QSAR, molecular simulations, PK/PD, systems biology, or ODE‑based models).\n\nHands‑on experience with model monitoring, drift detection, and automated retraining systems.\n\nFamiliarity with API gateway patterns, event‑driven architectures, and service mesh technologies.\n\nExperience with feature stores, data versioning (DVC), or experiment tracking at scale.\n\nExposure to AI agent frameworks (MCP, LangChain) or building APIs that AI systems invoke programmatically.\n\nExperience with C, C++, CUDA, or GPU‑accelerated computing for optimizing model training/inference performance; familiarity with containerizing HPC workloads (Singularity/Apptainer).\n\nLilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.\n\nLilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.\n\nActual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is $66,000 - $165,000. Full‑time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company‑sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well‑being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities). Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.\n\n#J-18808-Ljbffr","datePosted":"2026-06-17T03:38:22.833Z","dateModified":"2026-06-17T03:38:22.833Z","hiringOrganization":{"@type":"Organization","name":"Initial Therapeutics","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"8ac9cef284da604789f39b79"},"url":"https://jobsearcher.com/jobs/8ac9cef284da604789f39b79"}}