Applied Science Manager - Match & Affordances, Amazon Robotics
Core
Lead a team of applied scientists and engineers to develop intelligent robotic stow policies, placement optimization, and high-density storage solutions using machine learning and geometric reasoning.
Role type
Senior Applied Science Manager (Robotics & ML)
Builds
Scalable robotic stow strategies and warehouse capacity optimization systems
Domain
Robotics, Machine Learning, Optimization, Warehouse Automation
Deliverable
production ML models
Required skills
People leadership, technical vision setting, cross-functional collaboration, project delivery management, root cause analysis, deep learning, reinforcement learning, combinatorial optimization, geometric reasoning, transformer architectures
Preferred skills
Hiring and talent development, representation learning, affordance learning, scene-action understanding, VLAs, VLMs
Technologies
PyTorch, TensorFlow, MxNet
Responsibilities
Motivate, recruit, and retain top talent in ML and optimization; set technical roadmaps for stow policy and density improvements; guide research and deployment of ML/RL algorithms; collaborate with perception, motion planning, and hardware teams; manage project timelines and deliverables; troubleshoot policy regressions and optimization failures.
Seniority
Senior, hands-on IC with management responsibilities