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Platform Engineer, Biotech

Salary
$180K–$240K
Hiring from
United States
Work type
Hybrid
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About 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

  • Build and maintain cloud data platform components, including object storage, lakehouse architecture, catalogs, lineage, versioning, and access systems.

  • Design and operate governed data stores and releases for clinical records, molecular features, metadata, and linked datasets.

  • Develop reproducible bioinformatics pipelines for omics data, using containerized workflows and cloud batch compute.

  • Implement data quality checks, biological validation, and visualizations that help teams identify issues.

  • Prepare versioned, training-ready datasets and build data deployment interfaces for partner environments.

  • Operate production infrastructure, including Kubernetes, CI/CD, distributed workload scheduling, security, observability, reliability, and cost optimization.

What We're Looking For

  • 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.

  • Production experience operating Kubernetes, writing infrastructure as code with Terraform or similar tools, and shipping tested Python and/or Go code.

  • Experience designing CI/CD and deployment systems, job orchestration, and infrastructure for machine learning workloads; GPU or distributed training experience is valuable.

  • Familiarity with a major cloud provider, preferably AWS, plus workflow managers such as Nextflow, lakehouse and warehouse design, data catalogs, and orchestration.

  • 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.

  • 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.

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