About the job
The Amazon Robotics Autonomous Mobility software team is seeking an Applied Scientist to research and develop state-of-the-art algorithms and software that manage fleet of robotic systems. In this role you will apply the latest trends in research to solve real-world problems in scheduling and optimization to improve how a fleet of robots complete their tasks. You will collaborate with an exceptional team of scientists and engineers building a new generation of autonomous mobile robots to power the Amazon fulfillment and transportation networks.
Responsibilities
- Architect, design, and implement robotic applications and infrastructure.
- Influence the team's strategy and contribute to long-term vision and roadmap.
- Work with stakeholders across the organization to iterate on design and implementation.
- Maintain high standards by participating in reviews, designing for fault tolerance and operational excellence, and creating mechanisms for continuous improvement.
- Prototype and test concepts or features, both through simulation and emulators and with live robotic equipment
- Work directly with customers and partners to test prototypes and incorporate feedback
- Mentor other engineers on the team.
Qualifications
Minimum
- PhD, or Master's degree
- PhD in Engineering, Science, Technology, Computer Science, Mathematics or a related quantitative field (OR equivalent Masters Degree plus 4+ years experience in CS or related field)
- 1+ years of experience programming in Java, C++, Python or related language
- Relevant industry or academic applied research experience in developing optimization or scheduling algorithms for fleets of mobile robots.
- Experience building machine learning models or developing algorithms for business applications.
- Strong background in algorithms and hands-on experience developing algorithms for highly-scalable systems.
- Ability to work on a diverse team or with a diverse range of coworkers.
Preferred
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- PhD and 2+ years of relevant industry or academic research experience in developing scheduling and optimization algorithms.
- Extensive knowledge and practical research experience in one or more of the following areas: optimization, operations research, machine learning.
- 2+ years experience programming in Java, C++, Python or a related language, and experience building high-quality, scalable production software.
- Scientific mindset and the ability to invent and problem-solve.
- Excellent written and verbal communication skills with the ability to present complex technical information in a clear and concise manner to a variety of audiences.
- Publications at top-tier peer-reviewed conferences or journals
- Experience with mentoring other engineers.
- Demonstrated ability to design, implement, and test in a fast-paced environment