Platform Engineer, Biotech

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.

• 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.

Hybrid role based in San Francisco, California. Candidates must be based in or willing to relocate to San Francisco.

• 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.

Base salary: $180,000 to $240,000 annually. Visa sponsorship is not available.