# Staff+ Software Engineer, RL Data Platform

**Company**: Anthropic
**Location**: San Francisco, CA
**Work arrangement**: hybrid
**Experience**: staff
**Job type**: full-time
**Salary**: $320,000-$405,000 USD
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q116758847

**Apply**: https://job-boards.greenhouse.io/anthropic/jobs/5404730008?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_d78bb8fd-984

## Description

Anthropic's mission is to create reliable, interpretable, and steerable AI systems.

The RL Data Platform team builds the systems that produce, move, and serve the human data Claude learns from.

As a Staff+ Software Engineer on this team, you will design and ship web interfaces used by thousands of expert annotators, build the backend services and data pipelines behind them, and work directly with RL researchers to understand what data they need and why.

Key responsibilities:

- Design, build, and operate the feedback and data collection interfaces used by human annotators, domain experts, and internal researchers.

- Build and maintain the backend services, APIs, and pipelines that route model samples to humans and return structured feedback to training.

- Own the reliability, latency, and usability of systems that run continuously against live model endpoints.

- Partner with RL researchers to translate loosely specified data needs into well-scoped collection campaigns and the tooling to run them.

- Build dashboards, monitoring, and inspection tools so researchers can see data quality and throughput without asking an engineer.

- Identify and remove the bottlenecks between "we want this data" and "it's in the training mix".

Minimum qualifications:

- Strong full-stack engineering skills, with production experience in TypeScript/React on the frontend and Python on the backend.

- Experience designing and operating backend services and data pipelines that other teams depend on.

- A track record of owning projects end-to-end, from an ambiguous brief to something in production that people use.

- Comfort working directly with technical stakeholders whose needs change week to week, and the judgment to push back when something isn't worth building.

- Effective use of AI tools in your own day-to-day work.

- Care about the societal impacts of your work.

Preferred qualifications:

- Experience building annotation, labelling, evaluation, or other human-in-the-loop data tooling.

- Experience with RLHF, preference data, or other human-feedback pipelines for ML systems.

- Experience shipping researcher-facing or other expert-facing internal tools people love: interviewing users, hunting down friction, measurably improving the experience.

- Experience running experiments on data collection interfaces and using the results to improve data quality.

- Experience working with crowdworker or expert vendor platforms at scale.

- Familiarity with how LLMs are trained and evaluated.

The annual compensation range for this role is $320,000-$405,000 USD.

## Skills

### Required
- TypeScript
- React
- Python
- full-stack engineering
- backend services
- data pipelines

### Nice to have
- RLHF
- preference data
- human-feedback pipelines
- annotation tooling
- labelling
- evaluation
- human-in-the-loop data tooling

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/anthropic/jobs/5404730008?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)