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ClinLab Solutions Group Linkedin · Posted 19d ago

Computational Biology AI/ML Engineer

Indianapolis

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Indexed description

Job Title: Computational Biology AI/ML Engineer

Work Location: Marion County, IN or San Diego County, CA

Summary:

Seeking an AI/ML Engineer to build and maintain the machine learning infrastructure supporting advanced computational research in the life sciences. This role sits at the intersection of AI research and production systems, working cross-functionally to accelerate scientific discovery. Hybrid schedule with partial onsite presence required.

Responsibilities:

  • Build and maintain ML infrastructure, including automated pipelines for model training, evaluation, and deployment.
  • Manage and optimize compute resources across containerized and high-performance computing environments for large-scale training.
  • Design scalable data pipelines that process and deliver ML-ready datasets from diverse sources.
  • Develop tools and frameworks that enable rapid iteration on advanced modeling and generative AI approaches.
  • Architect distributed systems capable of supporting large multimodal datasets and foundational models.
  • Implement monitoring, logging, and alerting to ensure reliability, performance, and cost efficiency.
  • Partner with scientists and platform engineers to accelerate research and development workflows.
  • Apply DevOps best practices — infrastructure as code, version control, and collaborative workflows — to scientific computing environments.

Qualifications:

  • 5+ years of industry experience across software engineering, DevOps, data engineering, or ML engineering.
  • 3+ years of focused MLOps experience building and maintaining production-grade ML infrastructure.
  • Strong DevOps fundamentals and experience with modern CI/CD practices.
  • Hands-on experience deploying and managing containerized ML workloads.
  • Experience with job schedulers in HPC environments and distributed training optimization.
  • Strong Python skills and experience with leading ML frameworks.
  • Experience building ETL processes and scalable data pipelines; familiarity with major cloud platforms.
  • Preferred: experience with scientific or research data and modern AI/agentic tooling.


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