Senior Applied Scientist, Last Mile Robotics

Every doorstep is different. Our robot has to understand all of them.

We're building robots to deliver packages to customer homes. To make that possible, we're creating a system that can automatically generate a simulation-ready digital twin of the outdoor delivery environment for every customer home Amazon delivers to; modeling the driveways, yards, walkways, stairs, porches, and doorsteps a robot must understand and navigate.

And the goal isn't simply to create virtual worlds that look real. They need to be real in the ways that matter to a robot. Geometry, semantics, appearance, physical properties, and the varied environmental cues that influence perception, planning, and motion, must be reproduced faithfully so robot behaviors from the field are repeatable in simulation.

Our simulator becomes an effective tool to study the problem. The same autonomy software that runs on the physical robot also runs in simulation. When robot behavior differs between simulation and reality, we can ask why, and improve the representation, simulation, or models that produced the difference.

Our North Star ambition is a system capable of modeling the delivery environment for every customer home we serve, across the enormous diversity of real residential environments.

There isn't an established recipe for doing this. We are advancing the knowledge frontier of scene reconstruction. The right representation may combine classical geometry, learned scene representations, generative models, world models, or approaches that haven't been invented yet.

We're interested in people with deep expertise in one or more areas of: Computer vision, 3D graphics, scene reconstruction, physics simulation, neural scene representations, Gaussian splatting, generative AI, world models, or related areas - with a strong interest in applying that expertise to robotics.

Role Overview

This is applied research with a short distance from idea conception to physical consequence. You'll work closely with robotics, autonomy, simulation, and software engineers to turn promising methods into systems that change how real robots perceive, plan, and navigate at Amazon scale.

As an Applied Scientist on the Last Mile Robotics team, you will develop cutting-edge methods for capturing, reconstructing, and simulating real-world delivery environments in high-fidelity 3D. Your work will directly enable autonomous robots to understand and navigate the diverse conditions found at customer doorsteps. You will push the boundaries of scene reconstruction, neural rendering, and generative modeling, transforming scientific breakthroughs into physical impact through rapid experimentation and close collaboration with robotics, autonomy, and simulation teams.

About the team

We're a multidisciplinary team working across robotics, simulation, computer vision, graphics, machine learning, and software engineering.

We don't expect the best ideas to come from any one discipline. A graphics researcher, roboticist, computer-vision scientist, simulation expert, or machine-learning researcher may see a different path through the same problem, and we expect the strongest solutions to emerge from bringing those perspectives together.

We value technical depth, curiosity, rapid experimentation, and low-ego collaboration. We ask for help when we need it and give it generously when someone else does. We like problems where the answer isn't obvious and turning promising ideas into working systems.

Every doorstep is different. Help us build the technology that lets a robot understand all of them.

Basic qualifications

- 3+ years of building machine learning models for business application experience

- PhD, or Master's degree and 6+ years of applied research experience

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

- Experience with neural deep learning methods and machine learning

Preferred qualifications

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

- Experience with large scale distributed systems such as Hadoop, Spark etc.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. 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. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

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