Product Manager, Gen AI Platform

Scale AI
New York, NY; San Francisco, CAPosted 23 March 2026

Tech Stack

Job Description

Scale AI builds the data infrastructure that powers the world’s most advanced AI. We are the trusted data partner behind frontier model makers and enterprise AI teams — providing the high-quality training data, evaluation frameworks, and human-feedback systems that make models smarter, safer, and more capable. Scale operates as a two-sided marketplace. On the demand side , our customers — leading AI labs and enterprises — need precisely labeled, expert-curated data to train and evaluate their models. On the supply side , we work with a global network of 500,000+ skilled contributors across 100+ countries who perform the complex annotation, evaluation, and data-generation tasks that fuel AI progress. Product Managers at Scale sit at the intersection of these two sides, shaping the systems, tooling, and experiences that make this marketplace work at unprecedented quality and scale. We are hiring Product Managers across multiple teams within our GenAI organization. These roles span both demand-side products (the tools and platforms our customers interact with) and supply-side products (the systems that power our contributor ecosystem). Each role offers the opportunity to work on high-impact, technically complex problems at the frontier of AI — with dedicated engineering, design, and data science teams. About the Role Scale’s GenAI platform is how the world’s leading AI companies — from frontier model labs to Fortune 500 enterprises — create the training data that makes their models best-in-class. As a PM here, you are building the systems that directly shape AI model quality. These roles are deeply cross-functional. You will work with dedicated engineering, design, and data science teams, as well as operations, finance, growth, and customer-facing stakeholders. The problems are technically complex, the pace is fast, and the impact is measurable. Whether you are on the demand side (shaping the products customers use to create and evaluate training data) or the supply side (building the systems that power our global contributor marketplace), you will own your product area end-to-end — from strategy to execution to instrumentation. Scale is a growth-stage company with the resources of a well-funded leader and the urgency of a startup. PMs here operate with significant autonomy, ship frequently, and are expected to be deeply analytical and hands-on. Example Product Management Openings: Task UX (Demand Side) — Own the end-to-end tasking product. You will define how tasks are designed, how contributors interact with multi-turn chat interfaces, and how in-task quality is measured and enforced across diverse conversational modalities. This is a critical surface area for training the next generation of models. Multi-Dimensional Quality (Demand Side) — Own Scale’s MDQ measurement framework, the CoPilot assisted-annotation experience, and our data pipeline connectivity layer. You will drive the core data quality infrastructure that customers depend on — defining how quality is decomposed, measured, and surfaced, while building AI-assisted tooling that helps contributors produce higher-quality outputs faster. Pay Incentives (Supply Side) — This PM owns the payment and incentive systems that serve Scale’s global contributor base. You will ensure 500,000+ contributors across 100+ countries are paid accurately and on time, set pay rates methodically by skill and geography, and design incentive structures that balance cost efficiency, data quality, and contributor satisfaction. This role sits at the intersection of marketplace economics, global payments operations, and contributor experience. You Will Set the product strategy and roadmap for your area, grounded in customer needs, data analysis, and business impact Develop and execute a data-driven product roadmap through close collaboration with senior leadership, engineering, operations, data science, analytics, and design Translate customer and internal-user needs into clea ... (truncated, view full listing at source)
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