# Pre-training Distributed Systems Tech Lead / Manager at Anthropic

> Closed role observed by RunReq as of 2026-10-15T00:25:36.103105+00:00.

## Role details

- Company: [Anthropic](http://runreq.com/company/anthropic/index.md)
- Location: San Francisco, CA
- Team: AI Research & Engineering
- Compensation: $500K–$850K /YR
- First observed: 2026-07-23T01:30:48.491486+00:00
- Days open: 69
- Employer posting: [View the authoritative posting](https://job-boards.greenhouse.io/anthropic/jobs/5367417008)

## Shortened description

### Key responsibilities

- Lead a team that builds distributed systems to schedule, orchestrate, and execute evals for frontier model training.
- Own eval throughput and cost through compute allocation, queueing, caching, and reuse across constrained accelerator pools.
- Build researcher harnesses and ensure results are deterministic, reproducible, interpretable, and supported by uncertainty estimates.
- Manage and grow the team, prioritize its work, coach reports, and contribute directly as an engineer.

### Qualifications needed

- Lead technical projects on large scale distributed systems and have at least one year of experience managing engineers or tech lead with reports experience.
- Demonstrate strong Python and Rust skills and experience building high throughput, fault tolerant systems on cloud or on premises accelerator fleets.
- Hold a Bachelor’s degree or equivalent education, training, or experience in a relevant field.
- Preferred: Experience with LLM inference or training infrastructure, eval or benchmarking systems, statistical methods, observability, and regression detection.

## Hiring context

- Open roles on this team: 66
- Newly observed on this team in 30 days: 7
- Company median days open: 55

## Interpretation

- RunReq records observed job postings; it does not show applicant volume or completed hires.
- The linked employer posting is authoritative for the full description and application process.
- Human-readable job page: http://runreq.com/jobs/30d1f2e0-0b69-867c-9af9-77aee1bf3338
- Site-wide agent directory: http://runreq.com/llms.txt