Job Description

Bioinformatics Engineer - SF Onsite

I’m looking for world-class talent—people who set the bar, not just meet it. If you operate at this level or have the tenacity to get there, this role is for you.

This team has an extensive yet practical interview process. If you make it through, you'll be building scalable software solutions that enable biologists to analyze, visualize, and manage massive biological datasets—without writing code. This role requires being equal parts software engineer and bioinformatics expert, and developing cloud-based systems that bridge biotech and software. You must deliver high-quality engineering while clearly communicating complex bioinformatics concepts to researchers.

Success here demands bioinformatics expertise, cloud infrastructure knowledge, and software engineering skills—or the foundation, capacity, and discipline to get there fast.

Here is some of what you'd be working on:

Bioinformatics Data Analysis & Pipeline Development

• Experience processing and analyzing genomic, transcriptomic, proteomic, or metagenomic datasets (e.g., NGS, RNA-seq, single-cell data).
• Familiarity with workflow automation tools like Nextflow, Snakemake, or CWL.

Proficiency in Programming & Databases

• Strong coding skills in Python (backend), TypeScript (frontend), and SQL (PostgreSQL database management).
• Experience designing efficient, scalable bioinformatics software and data structures.

Cloud Computing & Distributed Systems

• Experience working with AWS (S3, EC2, Lambda), Kubernetes, and Terraform for managing large-scale biological data.
• Understanding of horizontal scaling, distributed file systems (FUSE, state machines), and cloud cost optimization.

Containerization & DevOps Practices

• Expertise with Docker, Kubernetes, systemd, and CI/CD pipelines for reproducible bioinformatics workflows.
• Knowledge of cloud-based infrastructure automation (Terraform, Kustomize, Helm charts).

Machine Learning & AI for Bioinformatics (Bonus but Highly Valuable)

• Experience applying ML models to biological datasets (e.g., variant calling, biomarker discovery, sequence alignment).
• Familiarity with TensorFlow, PyTorch, or Scikit-learn for computational biology applications.

Software Engineering Best Practices & API Development

• Experience with React.js (UI frameworks), GraphQL (data queries), and API development.
• Strong understanding of code quality, static typing, and system performance optimization.

This team’s culture is built on excellence, ownership, and relentless growth. It’s a small, high-caliber group that moves fast, values intellectual curiosity, and thrives on solving complex problems. Engineers are given real responsibility from day one, with a strong emphasis on mentorship, continuous learning, and craftsmanship in code.

They operate in a meritocratic environment where impact matters more than titles, and the best ideas win—regardless of where they come from. Collaboration is key, but so is autonomy; they expect everyone to take initiative, challenge assumptions, and push boundaries. If you’re someone who’s driven by innovation, ownership, and the pursuit of mastery, you’ll fit right in.

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