Staff Research Engineer, Discovery Team

Anthropic · San Francisco, CA · AI Research & Engineering · listed April 23, 2025

The shape of it

Seniority
Staff
Experience asked
8+ years
Where
Hybrid
Stated pay
$350,000 – $850,000 USD
Requirements listed
8
Length
1,033 words

In the posting’s own words

As a Research Engineer on our team you will work end to end, identifying and addressing key blockers on the path to scientific AGI. Strong candidates should have familiarity with language model training, evaluation, and inference, be comfortable triaging research ideas and diagnosing problems and enjoy working collaboratively. Familiarity with performance optimization, distributed systems, vm/sandboxing/container deployment, and large scale data pipelines is highly encouraged.

What it asks for · 8

  • Have 8+ years of ML research experience
  • Are familiar with large scale language model training, evaluation, and inference pipelines
  • Enjoy obsessively iterating on immediate blockers towards longterm goals
  • Thrive working collaboratively to solve problems
  • Have expertise in performance optimization and distributed computing systems
  • Show strong problem-solving skills and ability to identify technical bottlenecks in complex systems
  • Can translate research concepts into scalable engineering solutions
  • Have a track record of shipping ML systems that tackle challenging multi-step reasoning problems

Also a plus

  • Expertise with performance optimization for language model inference and training
  • Experience with computer use automation and agentic AI systems
  • A history working on reinforcement learning approaches for complex task completion
  • Knowledge of containerization technologies (Docker, Kubernetes) and cloud deployment at scale
  • Demonstrated ability to work across multiple domains (language modeling, systems engineering, scientific computing)
  • Have experience with VM/sandboxing/container deployment and large-scale data processing
  • Experience working with large scale data problem solving and infrastructure
  • Published research or practical experience in scientific AI applications or long-horizon reasoning

What the job covers

  • Working across the full stack to identify and remove bottlenecks preventing progress toward scientific AGI
  • Develop approaches to address long-horizon task completion and complex reasoning challenges essential for scientific discovery
  • Scaling research ideas from prototype to production
  • Create benchmarks and evaluation frameworks to measure model capabilities in scientific workflows and computer use
  • Implement distributed training systems and performance optimizations to support large-scale model development

Tools and skills named

Models & research
  • Inference3×
  • Machine learning2×
  • Reinforcement learning
Cloud & infra
  • Distributed systems
  • Docker
  • Kubernetes
Data
  • Data pipelines

Words the posting leans on

  • systems9×
  • scientific8×
  • model7×
  • research6×
  • experience5×
  • problems4×
  • reasoning4×
  • training4×
  • blockers3×
  • complex3×
  • computer3×
  • distributed3×
  • inference3×
  • language model3×
  • large scale3×
  • performance optimization3×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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How this page was made

An automated read of a public job posting, fetched August 24, 2026 and last changed by Anthropic on August 21, 2026. Every list above is pulled from the posting’s own sentences — nothing rewritten, nothing added, no judgment about the role or the company. Counts and seniority are read off the text by rule, so they can be wrong where the posting is unusual. The original is the only thing that binds. Openings close without warning; check the source before spending an evening on it.