Jobs · Engineering · Massachusetts

Applied Scientist - Fleet Scheduling and Optimization, Amazon Robotics, Autonomous Mobility

Amazon · North Reading, MA · 5 days ago
EngineeringFull-time

Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers that work passionately to apply leading advances in robotics and software to solve real-world challenges that will transform our customers’ experiences. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun.

About the role

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 a 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

  • PhD, or Master's degree 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 Qualifications

  • 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.

Benefits

  • Medical, Dental, and Vision Coverage.
  • Maternity and Parental Leave Options.
  • Paid Time Off (PTO).
  • 401(k) Plan.

Pay

USA, MA, North Reading - $142,800.00 - $193,200.00 USD annually. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location.

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