Applied Scientist II, Amazon Robotics · Applied Science

The Amazon Robotics team is seeking an experienced Applied Scientist to join our team. In this role you will apply the latest trends in research to solve real-world problems in robotics and AI. You will collaborate with a team of scientists and engineers building these applications. We holistically design, build, and deliver end-to-end robotic systems. Our team is also responsible for core infrastructure and tools that serve as the backbone of our robotic applications, enabling roboticists, machine learning scientists, software engineers, and hardware engineers to collaborate and deploy systems in the field.

Key job responsibilities

• Research, design, implement and evaluate complex perception, motion planning, and decision making algorithms integrating across multiple disciplines and leveraging machine learning.

• Create experiments and prototype implementations of new learning algorithms and prediction techniques.

• Work closely with software engineering team members to drive scalable, real-time implementations.

• Collaborate with machine learning and robotic controls experts to implement and deploy algorithms, such as machine learning models.

• Collaborate closely with hardware engineering team members on developing systems from prototyping to production level.

• 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.

About the team

Watch this video to learn more about Vulcan Pick team in Amazon Robotics: https://www.amazon.science/publications/vulcan-pick-a-robotic-system-for-picking-targeted-objects-from-fabric-pods

- PhD, or a Master's degree and experience in CS, CE, ML or related field

- Experience in building models for business application

- Experience in patents or publications at top-tier peer-reviewed conferences or journals

- Experience programming in Java, C++, Python or related language

- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

- Experience using Unix/Linux

- Experience in professional software development

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