Staff+ Software Engineer, RL Data Platform

Details

Anthropic's RL Data Platform team builds the systems that produce, move, and serve the human data Claude learns from, including feedback interfaces, pipelines that turn feedback into training signals, and researcher tooling for launching, monitoring, and inspecting data collection. This is a full-stack role involving web interfaces, backend services, data pipelines, and collaboration with RL researchers.

Responsibilities

• Design, build, and operate feedback and data collection interfaces for human annotators, domain experts, and internal researchers.
• Build and maintain backend services, APIs, and pipelines that route model samples to humans and return structured feedback for training.
• Own the reliability, latency, and usability of systems operating continuously against live model endpoints.
• Partner with RL researchers to translate data requirements into collection campaigns and supporting tools.
• Build dashboards, monitoring, and inspection tools for evaluating data quality and throughput.
• Identify and remove bottlenecks between data requirements and inclusion in the training mix.

Requirements

• Strong full-stack engineering skills with production experience in TypeScript and React on the frontend and Python on the backend.
• Experience designing and operating backend services and data pipelines used by other teams.
• Experience owning projects end-to-end, from ambiguous requirements through production delivery.
• Ability to work directly with technical stakeholders and make sound prioritization decisions.
• Effective use of AI tools in day-to-day work.
• Care about the societal impacts of the work.

Preferred Qualifications

• Experience building annotation, labeling, evaluation, or other human-in-the-loop data tooling.
• Experience with RLHF, preference data, or human-feedback pipelines for machine learning systems.
• Experience building researcher-facing or expert-facing internal tools.
• Experience running experiments on data collection interfaces to improve data quality.
• Experience working with crowdworker or expert vendor platforms at scale.
• Familiarity with how LLMs are trained and evaluated.

Representative Projects

• Build interfaces for domain experts to review agentic transcripts, identify errors, and create corrected continuations in a training-ready format.
• Improve sampling paths between feedback interfaces and model endpoints.
• Build campaign launchers for configuring data collection efforts without writing code.
• Instrument annotator behavior to detect low-effort or adversarial work.
• Design data models and pipelines for new types of feedback.

Education and Logistics

• Minimum education: Bachelor's degree or an equivalent combination of education, training, and experience.
• Required field of study: A field relevant to the role, demonstrated through coursework, training, or professional experience.
• Experience requirements correlate with the internal job level.
• Hybrid policy: Staff are expected to work from an Anthropic office at least 25% of the time, although some roles may require more time in the office.

Benefits

Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office collaboration space.