Platform Engineer, Biotech
At a glance
Mid-level Platform & Infrastructure role at Clera. San Francisco · full-time · $180,000–$240,000 base.
devopsroles summary, based on the employer's posting.
What you'll do
- Build cloud data foundations for storage, lakehouses, catalogs, lineage, dataset versions and access
- Operate Kubernetes and create infrastructure-as-code, release pipelines and deployment systems for live workloads
- Create repeatable workflows for genomics, proteomics and other biomedical data, using cloud batch computing
- Use biological checks and visualizations to flag data or workflow problems, then ready versioned datasets for models and partners
- Keep platforms reliable, observable, secure and cost-aware, including infrastructure for GPU and distributed ML workloads
What you bring
- You have two to five years building data infrastructure and production pipelines, preferably in biotech or a related field
- You have run Kubernetes in production and built infrastructure as code with Terraform or a comparable tool
- You write Python or Go and have delivered tested, documented software for production
- You have designed CI/CD and deployment systems, along with scheduling or orchestration for distributed work
Who this fits
This mid-level role suits an engineer focused on production infrastructure and biomedical data pipelines. You must be in San Francisco or willing to relocate; the job is hybrid in San Francisco. Visa sponsorship is unavailable.
From the employer
About the Role
Join a team building cloud infrastructure for biomedical data and machine learning. You will develop and operate secure, reliable platforms and pipelines that make clinical and biological data usable for research and model deployment.
What You'll Do
Build and maintain cloud data platforms, including storage, lakehouse architecture, catalogs, lineage, dataset versioning, and access layers.
Design and operate Kubernetes clusters, infrastructure-as-code systems, CI/CD pipelines, and deployment systems for production workloads.
Create and maintain reproducible bioinformatics pipelines for genomics, proteomics, and other biomedical data using workflow tools and cloud batch compute.
Build data quality checks, biological validation, and visualizations that help teams identify issues in datasets and pipeline outputs.
Develop orchestration and scheduling for distributed workloads, and prepare versioned datasets for model training and partner deployment.
Own infrastructure reliability, observability, security, and cost optimization, including support for GPU and distributed machine learning workloads.
What We're Looking For
Two to five years of experience building data infrastructure and production pipelines, ideally in biotech, diagnostics, biobanking, health data, or a related field.
Production experience operating Kubernetes clusters and building infrastructure as code with Terraform or similar tools.
Strong Python and/or Go programming skills, with experience shipping tested, documented production code.
Experience designing CI/CD and deployment systems, and building orchestration or scheduling for distributed workloads.
Familiarity with AWS or another major cloud provider, Docker, Nextflow or similar workflow managers, lakehouses, data warehouses, and data catalogs.
Experience with sensitive clinical or biological data and standards such as OMOP or FHIR is valuable; R and SQL are also useful.
Experience with GPU infrastructure, distributed training, or large-scale data pipelines is a plus.
Based in San Francisco or willing to relocate.
Compensation & Benefits
Base salary: $180,000 to $240,000 annually. Visa sponsorship is not available.
Location
Hybrid in San Francisco, California, United States.
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