# Staff Research Engineer, Multi-Agent Scaling

**Company**: Anthropic
**Location**: San Francisco, CA
**Work arrangement**: hybrid
**Experience**: staff
**Job type**: full-time
**Salary**: $500,000-$850,000 USD
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q116758847

**Apply**: https://job-boards.greenhouse.io/anthropic/jobs/5442680008?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_9f917856-8a4

## Description

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole.

Large teams of agents are starting to solve problems no single agent can, from rewriting major codebases to formalizing landmark mathematics. Our team studies how these teams scale: what happens to performance, cost and coordination as the number of agents, the compute budget and the length of the task grow, and what has to change to keep getting returns from that scale.

## Responsibilities:

- Design, run and interpret large-scale experiments on agent teams, reasoning rigorously about what the data does and doesn't show

- Investigate how performance and efficiency change as team size, compute and task horizon grow, and find the bottlenecks that limit them

- Build and scale the systems that run very large agent teams reliably, and debug the failures that only appear at scale

- Design evaluations for long-horizon problems, and keep their results trustworthy

- Build the tooling and metrics that let researchers see what a large agent team is doing and why

- Partner with research teams across Anthropic so they can run their own experiments on the platform, and communicate findings clearly

## Requirements:

- Significant software engineering, ML or research engineering experience

- Owned something substantial end to end, such as a large system, an evaluation or benchmark, an agent product, or a research project

- Genuinely enjoy both research and engineering work

- Think quantitatively about complex systems, and think twice before trusting a number

- Can work from a vague question rather than a spec

- Are results-oriented, with a bias towards flexibility and impact

- Have clear written and verbal communication

- Care about the societal impacts of your work

## Nice to Have:

- Experience building or operating large-scale distributed systems

- Built evaluations, benchmarks or harnesses for LLMs or agents

- Experience building complex agentic systems that use LLMs

- Experience with scaling laws or other large-scale empirical research

- A background in operations research, statistics, economics, physics, quantitative finance, or another field that models and optimizes complex systems

The annual compensation range for this role is $500,000-$850,000 USD.

## Logistics:

- Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

- Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

- Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

- Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time.

## Benefits:

- Competitive compensation and benefits

- Optional equity donation matching

- Generous vacation and parental leave

- Flexible working hours

- A lovely office space in which to collaborate with colleagues

## Skills

### Required
- software engineering
- ML
- research engineering
- quantitative analysis
- complex systems

### Nice to have
- large-scale distributed systems
- evaluations
- benchmarks
- LLMs
- agents
- scaling laws
- operations research
- statistics
- economics
- physics
- quantitative finance

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/anthropic/jobs/5442680008?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)