Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
TypeScript @ 3
Python @ 3
AI @ 2
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Anthropic’s Human Data Interfaces team builds the systems that collect data to improve models. This includes novel interfaces for data vendors, tooling, and front-end and back-end infrastructure that enables researchers to gather high-quality data at scale. As a Software Engineer on this team you will own the architecture and execution of data collection pipelines — designing systems that are performant at scale and resilient to changing research needs. You will work closely with researchers, cross-functional data operations partners, and the crowdworkers and vendors who use these tools.
Responsibilities
- Architect and build data collection pipelines that support rapid iteration while balancing data quality and system maintainability
- Design interfaces for crowdworkers and vendors that are clear, efficient, and produce high-quality data
- Collaborate with research teams to understand evolving data needs and iterate quickly on collection methods
- Partner with Human Data Operations to understand end-to-end workflows and design helpful interfaces
- Prioritize and manage multiple workstreams, making trade-offs in a fast-moving research environment
Requirements
- At least a Bachelor's degree in a related field or equivalent experience
- Strong full-stack engineering experience with broad experience across the stack
- Experience building internal tools and working with users to understand their needs
- Experience designing and building front-end and back-end infrastructure and data collection pipelines
- Ability to balance rapid iteration with long-term system health and to operate in fast-moving environments
- Strong instincts around system design and building systems that evolve gracefully
- Comfortable working closely with researchers and cross-functional teams
Nice to Have / Strong Candidates May Also Have
- Experience building human data labeling interfaces, human-in-the-loop systems, or annotation workflows
- Familiarity with how preference data and reward models are used in AI model training
- Experience improving user experience for user-facing applications with complex UI interactions
- Experience influencing technical and product direction on a team
Logistics
- Annual Salary: $320,000 - $405,000 USD
- Location-based hybrid policy: all staff expected to be in one of our offices at least 25% of the time
- Interview languages: Python or TypeScript
- Visa sponsorship: Anthropic states they do sponsor visas and retain an immigration lawyer to assist
Benefits
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation and parental leave
- Flexible working hours
- Office space in which to collaborate with colleagues