Applied Science Manager - Match & Affordances, Amazon Robotics

Key job responsibilities

• People Leadership: Prioritize being a great people manager - motivating, rewarding, and coaching your diverse team is the most important part of this role. Recruit and retain top talent in machine learning, optimization, and decision systems. Excel in day-to-day people and performance management tasks.
• Technical Vision: Set a vision for your team and create technical roadmaps focused on stow policy development, placement optimization, and density improvements. Guide research, design, deployment, and evaluation of ML and RL algorithms, optimization methods, and geometric reasoning systems that inform robot action selection.
• Cross-functional Collaboration: Work closely with perception, motion planning, hardware, and fulfillment teams to create integrated solutions that maximize storage density while maintaining operational reliability. Partner with computer vision teams on 3D scene understanding and container geometry representation that drives policy learning.
• Delivery Excellence: Implement best practices in applied research and software development. Manage project timelines, resources, and deliverables effectively. Keep technical skills current to contribute meaningfully to architecture and design discussions.
• Problem Solving: Regularly participate in deep-dive troubleshooting exercises and drive technical post-mortem discussions to identify root causes of policy regressions, optimization failures, and KPI degradations.

Basic Qualifications

• PhD, or Master's degree and 4+ years of industry or academic research experience
• 6+ years of applied research experience
• 3+ years of scientists or machine learning engineers management experience
• Experience building machine learning models or developing algorithms for business application
• Experience with deep learning libraries such as PyTorch, TensorFlow, MxNet
• Research publications in computer vision, deep learning or machine learning at peer-reviewed workshops, conferences or journals
• Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations

Preferred Qualifications

• Experience hiring and growing top talent
• Experience in representation learning, and reinforcement learning in robotics systems
• Familiarity with the developments in the VLAs, VLMs, affordance learning and scene-action understanding

About The Team

Watch this video to learn more about Vulcan program in Amazon Robotics: https://www.amazon.science/latest-news/how-amazon-robotics-researchers-are-solving-a-beautiful-problem

Company

• Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Benefits

• Medical, Dental, and Vision Coverage
• Maternity and Parental Leave Options
• Paid Time Off (PTO)
• 401(k) Plan