Product Manager, Gen AI

Scale AI Scale AI · Data AI · San Francisco, CA · Gen AI EPD

Product Manager for GenAI at Scale AI, focusing on building data infrastructure and tooling for AI model training and evaluation. The role involves shaping products for both customers (demand side) and contributors (supply side), requiring end-to-end product ownership from strategy to execution. The position is cross-functional, working with engineering, design, and data science teams in a fast-paced, growth-stage environment.

What you'd actually do

  1. Set the product strategy and roadmap for your area, grounded in customer needs, data analysis, and business impact
  2. Develop and execute a data-driven product roadmap through close collaboration with senior leadership, engineering, operations, data science, analytics, and design
  3. Translate customer and internal-user needs into clear, well-defined functional and technical requirements backed by data analysis and deep understanding of your users
  4. 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
  5. Build long-term instrumentation, monitoring, and evaluation capabilities for product performance tracking and insight generation

Skills

Required

  • 4–10 years of experience in Product Management in the tech industry
  • Strong business acumen and analytical rigor
  • 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
  • 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

What the JD emphasized

  • building the systems that directly shape AI model quality
  • own your product area end-to-end
  • deeply analytical and hands-on
  • define how tasks are designed
  • how in-task quality is measured and enforced
  • drive the core data quality infrastructure
  • defining how quality is decomposed, measured, and surfaced
  • build AI-assisted tooling
  • ensure 500,000+ contributors across 100+ countries are paid accurately and on time
  • design incentive structures that balance cost efficiency, data quality, and contributor satisfaction
  • Experience translating complex technical systems into clear product strategies
  • Experience building products from the ground up and iterating through the scaling journey of a business

Other signals

  • building systems that directly shape AI model quality
  • shaping the products customers use to create and evaluate training data
  • building the systems that power our global contributor marketplace
  • own your product area end-to-end — from strategy to execution to instrumentation