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

Amazon Amazon · Big Tech · San Francisco, CA · Machine Learning Science

This role focuses on foundational research and building intelligent robotic systems, operating at the intersection of AI research and robotics. The individual will conduct original research, publish findings, and deploy innovations into production systems at Amazon scale. Key areas include developing foundation models, full-stack robotics systems, locomotion, manipulation, perception, sim2real transfer, multi-modal and multi-task robot learning, and designing frameworks that bridge research and deployment.

What you'd actually do

  1. Drive independent research initiatives across the robotics stack, including robot co-design, dexterous manipulation mechanisms, innovative actuation strategies, state estimation, low-level control, system identification, reinforcement learning, sim-to-real transfer, as well as foundation models focusing on breakthrough approaches in perception, and manipulation, for example open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization
  2. Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish
  3. Guide technical direction for full-stack robotics projects from conceptualization through deployment, taking a system-level approach that integrates hardware considerations with algorithmic development, ensuring robust performance in production environments
  4. Collaborate with platform and hardware teams to ensure seamless integration across the entire robotics stack, optimizing and scaling models for real-world applications
  5. Contribute to team's technical decisions and influence implementation strategies to help shape our approach to next-generation robotics challenges

Skills

Required

  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience with any programming language such as Python, Java, C++
  • Experience building machine learning models or developing algorithms for business application
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals
  • Experience developing and implementing deep learning models and applying theoretical models in an applied environment

Nice to have

  • Prior industry or academic research experience and demonstrated expertise in deep learning and large-scale robotics system development
  • Extensive programming skills in Python and PyTorch/JAX
  • History of impactful first-author publications at major or top-tier Robotics/ML/AI

What the JD emphasized

  • original research
  • publishing
  • deploying your innovations into production systems at Amazon scale
  • push the boundaries of what’s possible
  • take full ownership of turning breakthrough ideas into working systems
  • world-renowned AI pioneers
  • push the boundaries of what's possible in robotic intelligence
  • breakthrough foundation models
  • full-stack robotics systems
  • perceive, understand, and interact with the world in unprecedented ways
  • independent research initiatives
  • locomotion
  • manipulation
  • perception
  • sim2real transfer
  • multi-modal
  • multi-task robot learning
  • novel frameworks
  • state-of-the-art research
  • real-world deployment at Amazon scale
  • innovative technical exploration
  • practical implementation
  • platform teams
  • robustly in dynamic real-world environments
  • ambitious research directions
  • Amazon’s vast computational resources
  • ambiguous problems
  • very large multi-modal robotic foundation models
  • efficient, promptable model architectures
  • diverse robotic applications
  • novel foundation model architectures
  • innovative systems and algorithms
  • extensive infrastructure
  • prototype and evaluate at scale
  • world-class research team
  • complex technical challenges
  • full robotics stack
  • focused technical initiatives
  • conception through deployment
  • successful integration with production systems
  • technical discussions
  • brainstorming sessions
  • team leaders
  • fellow researchers
  • key stakeholders
  • experiments
  • prototype new ideas
  • massive compute cluster
  • extensive robotics infrastructure
  • Transform theoretical insights into practical solutions
  • handle the complexities of real-world robotics applications
  • reimagining it from the ground up
  • future of intelligent robotics
  • innovative foundation models
  • end-to-end learned systems
  • challenging problems in AI and robotics
  • sophisticated perception systems
  • adaptive manipulation strategies
  • complex, real-world scenarios
  • unique combination of ambitious research vision
  • practical impact
  • Amazon's massive computational infrastructure
  • rich real-world datasets
  • train and deploy state-of-the-art foundation models
  • full spectrum of robotics intelligence
  • multimodal perception
  • images
  • videos
  • sensor data
  • sophisticated manipulation strategies
  • diverse real-world scenarios
  • 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
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience with any programming language such as Python, Java, C++
  • Experience building machine learning models or developing algorithms for business application
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals
  • Experience developing and implementing deep learning models and applying theoretical models in an applied environment
  • Prior industry or academic research experience and demonstrated expertise in deep learning and large-scale robotics system development
  • Extensive programming skills in Python and PyTorch/JAX
  • History of impactful first-author publications at major or top-tier Robotics/ML/AI

Other signals

  • foundational research
  • intelligent robotic systems
  • foundation models
  • full-stack robotics systems
  • multi-modal
  • multi-task robot learning
  • reinforcement learning
  • sim-to-real transfer
  • end-to-end vision-language-action models