Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world's most important decisions.

We’re looking for a Senior AI Product Manager to own and scale Scale’s SEAL Leaderboard portfolio. In this role, you will define the strategy, roadmap, and operational excellence of Scale’s evaluation products, benchmarks, and public/private leaderboards. You will work across AI Product Management, ML Researchers, Engineering, Operations, and Go-To-Market teams to transform cutting-edge model evaluations into trusted industry benchmarks that influence model development and purchasing decisions across the AI ecosystem.

You will serve as the product owner for leaderboard initiatives, driving benchmark innovation, governance, infrastructure, customer adoption, and business impact. You will work directly with leading AI labs and enterprise customers, representing Scale as a thought leader in AI evaluation and measurement.

The ideal candidate combines strong product judgment, technical fluency, operational rigor, and customer-facing experience, with a passion for turning emerging model capabilities into scalable evaluation products.

You Will

• Own the roadmap and strategy for Scale’s SEAL Leaderboard portfolio, defining priorities across benchmark development, leaderboard launches, infrastructure investments, and product expansion.
• Facilitate the Leaderboard Steering Committee and drive alignment across AI-PM, ML, Engineering, Operations, and GTM stakeholders.
• Evaluate, prioritize, and operationalize new leaderboard proposals, ensuring alignment with customer demand, market opportunities, and company strategy.
• Define and manage the end-to-end leaderboard product lifecycle, from ideation and benchmark design to launch, growth, maintenance, and sunset decisions.
• Partner with ML researchers and domain experts to develop trustworthy evaluation methodologies, benchmark specifications, and leaderboard scoring frameworks.
• Drive the roadmap for leaderboard infrastructure, automation, and operational tooling to improve scalability, reduce manual effort, and accelerate benchmark releases.
• Establish governance processes for benchmark quality, evaluation integrity, release management, auditability, and update cadence.
• Work directly with frontier AI labs and enterprise customers to understand evaluation needs, gather feedback, and influence future leaderboard investments.
• Track adoption, usage, customer impact, and business outcomes, using data-driven insights to guide roadmap decisions and resource allocation.
• Identify new evaluation categories, benchmark opportunities, and leaderboard products that strengthen Scale’s industry leadership and create new revenue opportunities.
• Collaborate closely with GTM teams to support customer engagements, thought leadership initiatives, product launches, and strategic partnerships.

Ideally, You’d Have

• 5+ years of experience in product management, technical program management, consulting, or customer-facing technical roles.
• Strong technical fluency, including familiarity with machine learning systems, AI model evaluation, benchmarking, or data products.
• Experience building and scaling products that require coordination across engineering, operations, and business teams.
• Excellent stakeholder management and executive communication skills, with a demonstrated ability to drive alignment across cross-functional organizations.
• Strong analytical skills and the ability to translate ambiguous market and customer signals into clear product strategy.
• Experience working with AI researchers, ML teams, or evaluation frameworks is strongly preferred.
• Entrepreneurial mindset with a track record of creating new products, programs, or business initiatives from the ground up.
• Bias for action and comfort operating in fast-moving, ambiguous environments.
• Passion for advancing trustworthy AI evaluation and helping define industry standards for measuring frontier model capabilities.