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 clear, well-defined functional and technical requirements backed by data analysis and deep understanding of your users
- Guide and interface closely with engineering and data teams to define scope, review and refine technical capabilities, prioritize projects for release, and identify new opportunities
- Build long-term instrumentation, monitoring, and evaluation capabilities for product performance tracking and insight generation
- Establish business cases and projected return on investment to identify and prioritize opportunities
- Partner with finance and business leaders to manage impact on the profitability and growth of the overall business
- Communicate product vision, strategy, and progress to executive stakeholders and cross-functional partners
Ideally, You’d Have
- 4–10 years of experience in Product Management in the tech industry, with scope appropriate to level (L4: 4–6 yrs, L5: 6–8 yrs, L6: 8–10+ yrs)
- Strong business acumen and analytical rigor, with demonstrated success driving products in ambiguous, high-growth environments
- Experience translating complex technical systems into clear product strategies — comfort engaging deeply with engineering and data science teams
- Excellent communication and stakeholder management skills, capable of influencing across technical and non-technical audiences
- Experience building products from the ground up and iterating through the scaling journey of a business
- Bachelor’s or advanced degree in a quantitative, engineering, or related discipline
Nice to Have:
- Experience in AI/ML, data infrastructure, or marketplace businesses
- Strong understanding of the AI landscape — model training workflows, data labeling, evaluation, and deployment
- Experience with global payment systems, contributor/gig-economy platforms, or trust & safety domains
- Experience working at high-growth startups or scaling consumer/enterprise platforms