Member of Technical Staff, Pm-t, Frontier AI & Robotics (far)

Amazon Amazon · Big Tech · San Francisco, CA · Project/Program/Product Management--Technical

Product Manager for Amazon's Frontier AI & Robotics (FAR) team, focusing on defining and executing the product vision for an AI-powered robotics platform. The role centers on data strategy for foundation model creation, building an ecosystem for acquiring, labeling, and improving physical AI datasets. Responsibilities include architecting a data flywheel from robot fleets, developing strategies for synthetic data generation using simulation, and ensuring data compliance and quality. The role acts as a bridge between research and engineering to deliver data-ready platform features.

What you'd actually do

  1. Define and execute the long-term product vision for FAR's AI-powered robotics platform.
  2. Champion our core data strategy for foundation model creation, building a partner and tool ecosystem to systematically acquire, label, and iteratively improve physical AI datasets.
  3. Architect a continuous data collection flywheel across deployed robot fleets, transforming real-world telemetry from edge operations back into high-fidelity training tokens.
  4. Lead the strategy to create high-fidelity synthesized datasets, utilizing advanced physics engines and simulation to generate diverse training tokens at massive scale.
  5. Partner with operations, privacy, legal, and security teams to build enterprise-grade data management pipelines that programmatically enforce data minimization, anonymization, and CCPA/GDPR compliance.

Skills

Required

  • Bachelor's degree in Computer Science, Engineering, or a related technical field
  • Experience with feature delivery and tradeoffs of a product
  • Experience with AI/ML technologies
  • 10+ years of experience in technical product management
  • Experience leading AI/ML platform or robotics product strategy
  • Experience owning/driving roadmap strategy and definition for AI/ML or robotics systems

Nice to have

  • Experience in robotics design, automation systems development, control systems design, or related product development
  • Advanced degree (MS/PhD) in AI, Machine Learning, Robotics, Computer Science, or a quantitative field
  • Experience building and scaling AI/ML platforms (MLOps, model training infrastructure, data pipelines) from zero-to-one
  • Experience working at the intersection of AI research and product commercialization - translating frontier science into customer-facing products
  • Demonstrated ability to partner with research scientists and lead through ambiguity in fast-moving technical domains
  • Experience with foundation models, deep learning systems, or computer vision at scale
  • Entrepreneurial experience building AI-first products or founding AI-focused ventures

What the JD emphasized

  • define and execute the long-term product vision
  • core data strategy
  • foundation model creation
  • physical AI datasets
  • continuous data collection flywheel
  • synthesized datasets
  • advanced physics engines and simulation
  • enterprise-grade data management pipelines
  • programmatically enforce data minimization, anonymization, and CCPA/GDPR compliance
  • strategic bridge between machine learning research scientists, simulation developers, robotics engineers, and hardware teams
  • building the future of intelligent robotics through frontier foundation models and end-to-end learned systems
  • tackle some of the most challenging problems in AI and robotics
  • unique combination of ambitious research vision and practical impact
  • leveraging Amazon's computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models
  • work spans the full spectrum of robotics intelligence
  • building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations
  • pushing the boundaries of what's possible in robotics
  • working with world-class researchers
  • seeing your innovations deployed at unprecedented scale
  • Experience leading AI/ML platform or robotics product strategy
  • Experience owning/driving roadmap strategy and definition for AI/ML or robotics systems
  • Experience building and scaling AI/ML platforms (MLOps, model training infrastructure, data pipelines) from zero-to-one
  • Experience working at the intersection of AI research and product commercialization - translating frontier science into customer-facing products
  • Demonstrated ability to partner with research scientists and lead through ambiguity in fast-moving technical domains

Other signals

  • product vision
  • data strategy
  • foundation models
  • robotics platform
  • physical AI datasets
  • continuous data collection flywheel
  • synthesized datasets
  • physics engines
  • simulation