Amazon Applied Scientist Amazon Robotics 

United States, Washington, Seattle 

160509634

Key job responsibilities
• Research, design, implement and evaluate complex motion planning, controls, and decision-making algorithms that improve the performance of systems deployed in real-world conditions.
• Apply recent advances in topics such as planning optimization, model-based controllers, or grasp affordance learning to our systems in the lab and in the field.
• Work closely with software engineers to drive scalable, real-time implementations.
• Collaborate with experts across disciplines including perception, hardware and software to create intelligent, integrated systems and solutions.
• Represent Amazon in academia community through publications and scientific presentations.
• Work with stakeholders across hardware, science, and operations teams to iterate on systems design and implementation.
A day in the life
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan

- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- • Relevant industry or academic research experience in developing algorithms for robotic motion planning, perception, decision making, control and developing robotic systems.

- PhD and 1+ year of relevant industry or academic applied research experience in developing algorithms for robotic motion planning, control and decision making.
- Experience with interdisciplinary developments that involve hardware, software, and algorithm synergistic design.
- Experience in one or more relevant technical areas: robotics, computer vision, machine learning, sensors, real-time systems, embedded systems, etc.
- Experience implementing machine learning-based control policies on real robotic systems, including reinforcement learning, imitation learning, or behavior cloning.
- Experience developing and debugging software on physical systems.