Anthropic's Human Data Interfaces team builds the systems that collect data to improve our models. As a Software Engineer, you will own the architecture and execution of our data collection pipelines—designing systems that are both performant at scale and resilient to the rapidly changing needs of our research teams. You will work closely with researchers, cross‑functional data operations partners, crowdworkers, and vendors to build interfaces that are clear, efficient, and produce high‑quality data. The role is hybrid, with staff required to be in one of our offices at least 25% of the time.
Software Engineer, Human Data Interface na Anthropic
Híbrido - San Francisco, CA, USA; New York City, NY, USA
Ver mais vagas na AnthropicSalary
USD 320,000 - 405,000
Requirements
Skills
- Strong full-stack engineer with broad experience across the stack
- Very good at building internal tools, including working with users of the tools to understand their needs
- Thrives in fast-moving environments where you need to balance speed of iteration with long-term system health
- Quick study—this team sits at the intersection of a large number of different complex technical systems that you'll need to understand (at a high level) to be effective
- Experience building human data labeling interfaces, human-in-the-loop systems, or data collection pipelines
- Familiarity with how preference data and reward models are used in AI model training
- Experience working with researchers who are internal users/customers
- Background in building, and improving the user-experience of user-facing applications, particularly those involving complex UI interactions or annotation workflows
- Strong instincts around system design — building things that evolve gracefully as requirements change
- Experience influencing technical and product direction on a team
Responsibilities
- Architect and build data collection pipelines that support rapid iteration, balancing data quality and system maintainability
- Think deeply about the experience of the crowdworkers and vendors using these systems, building interfaces that are clear, efficient, and lead to high-quality data
- Collaborate closely with research teams to understand evolving data needs and iterate quickly on collection methods
- Partner with our Human Data Operations team to understand the end-to-end data workflow and design interfaces that make their jobs easier
- Prioritize and juggle multiple workstreams, making trade-off decisions in a fast-moving environment where research priorities can shift quickly
Descubra se seu currículo está pronto para esta vaga
Veja como nossa IA pode otimizar seu currículo e aumentar suas chances de conseguir esta posição.