Senior Applied Scientist

Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models.

At Amazon, we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration.

Responsibilities

• Design and implement whole body control methods for balance, locomotion, and dexterous manipulation
• Utilize state-of-the-art methods in learned and model-based control
• Create robust and safe behaviors for different terrains and tasks
• Implement real-time controllers with stability guarantees
• Collaborate effectively with multi-disciplinary teams to co-design hardware and algorithms for loco-manipulation
• Mentor junior engineers and scientists

Requirements

• 3+ years of building machine learning models for business applications
• PhD, or Master's degree and 6+ years of applied research experience
• Experience programming in Java, C++, Python, or related language
• Experience with neural deep learning methods and machine learning
• Experience with methods for whole-body control such as hierarchical quadratic programming and model-predictive control
• Experience with imitation learning and reinforcement learning for whole-body control
• Experience with simulation environments such as IsaacLab, Mujoco, Drake, etc.
• Experience with developing and deploying code for real-time controllers
• Experience in state estimation from multiple sensor modalities

Preferred Qualifications

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, etc.
• Experience with large-scale distributed systems such as Hadoop, Spark, etc.
• PhD in Robotics, with a focus on whole-body control
• Experience with low-level joint torque/impedance control
• Experience with robotics frameworks for fast prototyping (Matlab, ROS, etc.)

Benefits

• Comprehensive health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance, and optional supplemental life plans)
• Employee Assistance Program (EAP) and Mental Health Support
• Medical Advice Line and Flexible Spending Accounts
• Adoption and Surrogacy Reimbursement coverage
• 401(k) matching
• Paid time off and parental leave
• Sign-on payments and restricted stock units (RSUs)

Pay

USA, MA, N.Reading - $167,100.00 - $226,100.00 USD annually