Tech Stack
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.
AI @ 4
Communication @ 7
Machine Learning @ 4
Prioritization @ 7
Product Management @ 4
Project Management @ 7
- 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 Platform team builds systems that collect data to improve AI models, including infrastructure for simulating real-world environments and tasks, interfaces for data vendors, and pipelines that enable researchers to gather high-quality data at scale. The role owns product direction for human data tooling and works across research teams, data operations, engineering, and external vendors.
Responsibilities
- Own product direction and prioritization across labeling interfaces, infrastructure investments, data quality, and operational visibility.
- Partner with engineering to scope and ship products quickly in a fast-moving prototyping environment.
- Develop an understanding of research and training approaches to identify high-leverage tooling investments.
- Identify patterns across one-off requests and promote reusable infrastructure.
- Participate in crowd worker and vendor sessions to understand workflow pain points.
- Define and track outcome-based KPIs, including time to launch data collection projects, end-to-end data quality scores, and impact on model evaluation scores.
Requirements
- Interest in helping ensure that advanced AI systems have a positive impact.
- Comfort working in ambiguous, high-stakes environments and defining product strategy.
- Experience shipping products while deeply understanding technical constraints.
- Experience working directly with research teams, ideally in AI or machine learning contexts.
- Ability to communicate with crowdworkers about workflows and research teams about data quality methodology.
- Ability to quickly understand complex technical systems at a high level.
- Interest in how humans interact with AI systems and in designing experiences that elicit high-quality data.
- Experience building data collection tools, annotation platforms, or human-in-the-loop pipelines is advantageous.
- Experience working with researchers as internal users or customers is advantageous.
- Strong product intuition, particularly for complex user interfaces and annotation workflows.
- Strong project management, prioritization, and cross-functional communication skills.
- Five or more years of product management experience, including launching new products and scaling existing products.
- Intellectual curiosity, autonomous learning ability, researcher empathy, product creativity, and a founder mentality.
- A bachelor's degree or equivalent combination of education, training, and experience.
Benefits
- Competitive compensation and benefits.
- Optional equity donation matching.
- Generous vacation and parental leave.
- Flexible working hours.
- Collaborative office space.
- Visa sponsorship may be available; Anthropic states that it makes every reasonable effort to obtain visas and retains an immigration lawyer to assist with sponsorship.
Work Policy
This is a location-based hybrid role. Staff are currently expected to work from an Anthropic office at least 25% of the time, although some roles may require more office time.
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