3 hours ago
Base Salary
$320k - $405k/yr
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 to training.
- Own the reliability, latency, and usability of systems operating continuously against live model endpoints.
- Partner with RL researchers to scope data collection campaigns and build the associated tooling.
- Build dashboards, monitoring, and inspection tools for data quality and throughput.
- Identify and remove bottlenecks between desired data collection and inclusion in the training mix.
- Own projects end-to-end from ambiguous briefs through production deployment and operation.
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.
- Track record of owning projects end-to-end and delivering production software.
- Ability to work directly with technical stakeholders whose needs change frequently and make sound prioritization decisions.
- Effective use of AI tools in day-to-day engineering work.
- Commitment to considering the societal impacts of the work.
- Preferred experience with annotation, labeling, evaluation, or human-in-the-loop data tooling.
- Preferred experience with RLHF, preference data, or human-feedback pipelines for machine learning systems.
- Preferred experience building researcher-facing or expert-facing internal tools and improving their usability through user research and experimentation.
- Preferred experience with crowdworker or expert vendor platforms at scale and familiarity with LLM training and evaluation.
- Bachelor’s degree or equivalent combination of education, training, and/or experience in a relevant field.
Benefits
- Annual salary range of $320,000—$405,000 USD.
- Hybrid policy requiring staff to work from an office at least 25% of the time, with some roles requiring more office time.
- Visa sponsorship may be available, with immigration lawyer support.
- Competitive benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office collaboration space.
Tech Stack
Categories
Data EngineeringFull Stack
About Anthropic
We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.