Software Engineer, Human Data Interface
Anthropic
Job Overview
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Job Description
About Anthropic
Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About The Role: Software Engineer, Human Data Interface
Anthropic's Human Data Interfaces team builds the systems that collect data to improve our models. As a Software Engineer, Human Data Interface, you will own the architecture and execution of our data collection pipelines. This involves 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, and the crowdworkers and vendors who use these tools day-to-day.
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.
You May Be a Good Fit If You
- Believe that advanced AI systems could have a transformative effect on the world and are interested in helping make sure that transformation goes well.
- Are a strong full-stack engineer with broad experience across the stack.
- Are very good at building internal tools, including working with users of the tools to understand their needs.
- Thrive in fast-moving environments where you need to balance speed of iteration with long-term system health.
- Are a 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.
Strong Candidates May Also Have
- Experience building human data labelling 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.
How We're Different
Anthropic believes that the highest-impact AI research will be big science, working as a single cohesive team on a few large-scale research efforts. We value impact—advancing our long-term goals of steerable, trustworthy AI—and view AI research as an empirical science. Our extremely collaborative group hosts frequent research discussions, and we greatly value communication skills. Our research directions include GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Key skills/competency
- Full-stack engineering
- Data pipeline architecture
- Human-in-the-loop systems
- User experience (UX) design
- Internal tool development
- Scalable system design
- AI model training data
- Research collaboration
- Data quality management
- Backend and Frontend development
How to Get Hired at Anthropic
- Research Anthropic's Mission: Study their commitment to reliable, interpretable, and steerable AI systems and their core values for beneficial AI.
- Tailor Your Resume: Highlight your full-stack engineering skills, experience with data collection pipelines, human data interfaces, and internal tool development.
- Showcase System Design Acumen: Prepare to discuss your experience architecting scalable, resilient systems that adapt to evolving research priorities.
- Demonstrate Collaboration & UX: Emphasize your ability to work with researchers and improve user experiences for complex applications and annotation workflows.
- Prepare for Technical Depth: Expect rigorous questions on backend, frontend, data architecture, and your understanding of AI model training data needs.
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