Job Description
Job DescriptionAbout the Role
Join a biotech AI engineering team building and operating data infrastructure that turns clinical, genomic, imaging, and other biomedical data into reliable assets for machine learning. This hands-on role supports data workflows from ingestion and analysis through model training and deployment to partner environments.
What You'll Do
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Build and maintain cloud data platform components, including object storage, lakehouse architecture, catalogs, lineage, versioning, and access systems.
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Design and operate governed data stores and releases for clinical records, molecular features, metadata, and linked datasets.
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Develop reproducible bioinformatics pipelines for omics data, using containerized workflows and cloud batch compute.
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Implement data quality checks, biological validation, and visualizations that help teams identify issues.
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Prepare versioned, training-ready datasets and build data deployment interfaces for partner environments.
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Operate production infrastructure, including Kubernetes, CI/CD, distributed workload scheduling, security, observability, reliability, and cost optimization.
What We're Looking For
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Two to five years building data infrastructure and production pipelines in biotech, diagnostics, biobanking, health data, or a related setting involving sensitive biological or clinical data.
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Production experience operating Kubernetes, writing infrastructure as code with Terraform or similar tools, and shipping tested Python and/or Go code.
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Experience designing CI/CD and deployment systems, job orchestration, and infrastructure for machine learning workloads; GPU or distributed training experience is valuable.
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Familiarity with a major cloud provider, preferably AWS, plus workflow managers such as Nextflow, lakehouse and warehouse design, data catalogs, and orchestration.
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Experience with large-scale data pipelines, bioinformatics or omics data such as WGS, RNA-seq, or proteomics; familiarity with OMOP, FHIR, R, or SQL is helpful.
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Understanding of compliance controls such as HIPAA, GDPR, or SOC 2, and strong engineering practices for testing, documentation, code review, and provenance.
Compensation & Benefits
Base salary: $180,000 to $240,000 annually. Visa sponsorship is not available.
Location
Hybrid role based in San Francisco, California. Candidates must be based in or willing to relocate to San Francisco.
Compensation Range: $180K - $240K