Product Management, Human Data Platform

About the role

Anthropic's Human Data Platform team builds systems designed to collect data that improves our models. This includes the infrastructure to simulate real-world environments and tasks, novel interfaces for data vendors to use, and the pipelines that enable researchers to gather high-quality data at scale.

Responsibilities

• Own the product direction for our human data tooling, with clear prioritization across labeling interfaces, infrastructure investments, data quality, and operational visibility
• Partner with engineering to scope and ship quickly, staying close to the work in a fast-moving prototyping environment
• Develop a deep understanding of research and training approaches to identify where tooling investments will have the highest leverage
• Identify patterns across one-off requests and push toward reusable infrastructure that compounds over time
• Sit in on crowd worker and vendor sessions to systematically understand pain points
• Define and track outcome-based KPIs: time-to-launch for new data collection projects, end-to-end data quality scores, and measurable impact on model evaluation scores

Requirements

• Believe that advanced AI systems could have a transformative effect on the world and are interested in helping make sure that transformation goes well
• Drawn to ambiguous, high-stakes environments where you’ll play a big role in defining the product strategy
• Shipped products where they had to deeply understand technical constraints, not just translate requirements
• Experience working directly with research teams, ideally in AI/ML contexts
• Equally comfortable talking to crowdworkers about their workflow and to research teams about data quality methodology
• 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
• An interest in how humans interact with AI systems and how to design experiences that elicit high-quality data

Qualifications

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Benefits

• Annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
• Annual Salary $305,000—$385,000 USD

Logistics

• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

How We're Different

• We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts.
• We value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles.
• We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science.
• We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time.
• The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Guidance on Candidates' AI Usage

Learn about our policy for using AI in our application process.