Applied Scientist, Amazon

• We are looking for applied scientists with expertise in any of the following:
• Computer vision (including but not limited to tracking, object recognition, visual SLAM, motion prediction, reconstruction)
• Machine learning (e.g. reinforcement learning, supervised learning, Bayesian methods, online learning systems, ML for robotics)
• PhD in engineering, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
• Experience programming in C++, C#, Python or related language
• Experience in one or more relevant technical areas: robotics, computer vision, machine learning, sensors, real-time systems, embedded systems, distributed systems, or simulation
• Extensive experience with physical hardware and robot simulators
• MSc in Mechanical Engineering

Desirable

• Seeking an experienced Applied Scientist
• In this role you will apply the latest trends in research to solve real-world problems
• You will collaborate with a team of scientists and engineers building these applications
• We are looking for scientists with interest in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems
• 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