Platform Engineer, Biotech
Confirmed on the employer's own hiring board on Nov 13, 2026. First seen by Alion on Nov 13, 2026. Clera scores B on the Alion truth index.
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.