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Member of Technical Staff (Research Engineer)

Anthrogen

San Francisco, CAFull-time$180–380K/yrPosted 3mo agoStill listed 3 days ago

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At a glance

Compensation
$180–380K/yr
Location
San Francisco, CA
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

Anthrogen seeks a Member of Technical Staff (Research Engineer) to build and scale frontier AI systems for biology, focusing on distributed training, GPU optimization, and high‑throughput data pipelines, while collaborating closely with researchers in San Francisco.

Skills & qualifications

RequiredNice to have

Skills

PythonC++Distributed TrainingGPU OptimizationHigh‑Throughput Data PipelinesInference ServingLarge‑Scale ML SystemsPyTorchJAXCUDAAI Coding ToolsCompetitive ProgrammingOpen‑Source Contributions

Full job description

About Anthrogen Anthrogen is engineering post-modality biology. Today's modalities reflect historical contingencies in biological progress, not fundamental categories. We develop the AI systems that design modular biological machines — and the experimental infrastructure to instantiate them. We're a small, high-density team in San Francisco building frontier AI and the biological systems to validate it, and we care most about people who move fast, go deep, and pick up whatever the problem needs. The role We're looking for exceptional engineers excited about frontier AI, especially for the sciences — irrespective of bio background. You'll build and scale the systems behind our models: distributed training, data infrastructure, and high-throughput inference, owning hard problems end to end. Biology is the domain, but this is a frontier systems job first. What you'll do

  • Build and scale distributed training, GPU optimization, and high-throughput data pipelines.

  • Own inference and serving systems that run at scale.

  • Work shoulder-to-shoulder with researchers, turning ideas into robust infrastructure.

  • Take hard, ambiguous problems from zero to production and own them end to end. Who you are

  • You can write exceptional, production-grade code (strong Python plus a systems language), demonstrable through shipped systems, open source, or competition results.

  • Hands-on with large-scale ML systems: distributed training, GPU optimization, high-throughput data pipelines, or inference and serving at scale.

  • High-agency, in person, and willing to do whatever the problem needs. Bonus points

  • A track record of shipping research infrastructure or working closely with researchers.

  • An AI-native workflow — you get real leverage from AI coding tools.

  • Competitive programming or olympiad background (IOI, ICPC, Putnam, and the like).

  • Meaningful open-source contributions to ML infrastructure (PyTorch, JAX, CUDA).

  • Genuine interest in biology and AI for science. Logistics Full-time, onsite in San Francisco. Equity: 0.05-0.5%.

How this job compares

Set against the 1,151 open Research Engineer jobs on Olive Jobs, counted October 29, 2026.

Pay
  • This posting$180–380K/yr
  • California median$184–350K/yr391 salary ranges
  • US median$148–260K/yr832 salary ranges

This range's midpoint, $280K, is 10% above the California median midpoint ($254K) — in the middle half of Research Engineer salary ranges in California.

Openings
Olive Jobs lists 566 open Research Engineer jobs in California and 1,151 across the US. 5% of them nationwide are listed as remote or flexible.
Hiring the most in California
Experience
Research Engineer postings that state a minimum ask for 3 years of experience at the median; the middle half ask for 2 to 5 years (661 postings).
Education
436 of the 1,151 open Research Engineer jobs (38%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on October 29, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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