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Careers at Amazon
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Postdoctoral Scientist, Amazon Robotics

27 Oct 2025
North Reading, MA, USA
Verified by Turrior

Content + Source + Freshness • 14 Dec 2025 • 95% confidence

87 / 100

Offer value

Exceptional value through innovative research opportunities in robotic systems within a leading tech organization.

  • Join a leading team innovating in robotics technology
  • Publish and present cutting-edge research
  • Collaborate with other experts in a vibrant scientific community
Pros
  • Opportunity to innovate in robotics and AI on a global stage
  • Exposure to interdisciplinary collaboration with top scientists
  • Chance to publish cutting-edge research
Cons
  • High expectations for research output and innovation
  • May require flexible hours to meet project demands
  • Intensive focus on specialized scientific expertise

Who it's for

Postdoctoral/Research • Office-based, collaborative environment

Good fit
  • Experienced researchers in AI and robotics
  • Scientists motivated by innovation and advancement
  • Individuals seeking a collaborative research environment
Not recommended for
  • Those without a relevant advanced degree
  • Candidates uncomfortable with a heavy research focus
  • Individuals seeking non-technical job roles

Motivation fit

Desire to contribute to significant advancements in roboticsInterest in working in high-tech research settingsMotivation to engage in collaborative knowledge sharing

Key skills

Robotic systems and AIMulti-agent planning techniquesResearch publication and communicationCollaborative problem-solving
Score: 87/100 AI verified analysis

About the job

Description

Amazon is looking for talented Postdoctoral Scientists to join the Research and AI Development team at Amazon Robotics for a one-year, full-time research position. This Postdoctoral Scientist will innovate in the areas of multi-agent planning and reinforcement learning for robotic systems. They will have the opportunity to address challenges related to the control and optimization of the world’s largest fleet of mobile robots under uncertainty, including policy learning for resource management in robotic storage systems.

At Amazon, we experiment and innovate relentlessly. Science is core in our offering to shoppers, advertisers and customers. Our scientists apply machine learning, optimization, causal modeling and game theory at scale to enhance the customer experience, help advertisers reach relevant audiences, and support brand building. We are seeking talented scientists to invent cutting-edge techniques in a variety of areas and innovate on behalf of shoppers, advertisers, and customers.

Required application materials:

* CV, which lists all peer-reviewed publications and conferences,
* Research statement that outlines your research achievements and future research interests, and
* A journal article or book chapter that demonstrates your domain expertise.

Key job responsibilities
In this role you will:
• Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community.
• Publish your innovation in top-tier academic venues and hone your presentation skills.
• Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.

A day in the life
On a typical day in this role you will work to progress your research projects, meet with engineering, systems, and solutions stakeholders, brainstorm with other scientists on the team, and participate in team processes. You will follow your multi-agent planning and reinforcement learning projects though the entire life cycle of design, implementation, evaluation, analysis, and will communicate your findings and results through publications in top-tier academic venues.

About the team
The Research and AI Development team at Amazon Robotics is a multi-disciplinary science team that includes scientists with backgrounds in planning and scheduling, grasping and manipulation, machine learning, and operations research. We develop novel planning algorithms and machine learning methods and apply them to real-word robotic warehouses, including: (1) Planning and coordinating the paths of thousands of robots (2) Dynamic allocation and scheduling of tasks to thousands of robots (3) Learning how to adapt system behavior to varying operating conditions and (4) Co-design of robotic logistics processes and the algorithms to optimize them.

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