# Staff Research Engineer, Discovery Team

**Company**: Anthropic
**Location**: San Francisco, CA
**Work arrangement**: hybrid
**Experience**: staff
**Job type**: full-time
**Salary**: $350,000-$850,000 USD
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q116758847

**Apply**: https://job-boards.greenhouse.io/anthropic/jobs/4593216008?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_bc627744-0f7

## Description

As a Research Engineer on our team you will work end to end, identifying and addressing key blockers on the path to scientific AGI.

Responsibilities:

- 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

You may be a good fit if you:

- 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

Strong candidates may also have:

- 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

The annual compensation range for this role is $350,000-$850,000 USD.

## Skills

### Required
- ML research
- large scale language model training
- performance optimization
- distributed computing systems
- problem-solving

### Nice to have
- computer use automation
- agentic AI systems
- reinforcement learning
- containerization technologies
- cloud deployment at scale
- scientific AI applications
- long-horizon reasoning

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/anthropic/jobs/4593216008?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)