Demo

Sr. Applied Scientist, Amazon Robotics

Amazon
Boston, MA Full Time
POSTED ON 6/3/2026
AVAILABLE BEFORE 8/3/2026

Description

Are you interested in how to build AI reasoning systems that give provably correct answers? Are you excited by science at the interface of classical AI reasoning and Large Language Models (LLMs)? Would you like to apply your technology to serve operations customers better?

Amazon Robotics is looking for a talented Applied Scientist in Neurosymbolic AI. You will innovate on combining language models (LMs) with classical AI reasoning. You will work with a team of scientists and engineers to achieve this. You will publish your results in papers at leading venues in AI. You will be part of a larger team and have the opportunity to work on problems such as: using LMs to generate plans, using AI reasoning to verify plan correctness, learning efficient reasoning strategies, self-improving models. You will work on basic science and on business problems in robotics, automation and fulfillment across our operations.

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

A day in the life
You'll meet regularly with your technical lead and your team on your ideas, get guidance and feedback, work together on architectures and algorithms, author papers, build AI systems, all with the aim of delivering results for your operations customers. You'll work closely with other scientists to review your plans and results. You'll meet with engineers to implement your ideas at scale.

About the team
The Veritas team is a science team working at the boundary between language models and classical AI reasoning. We work across on customer problems in fulfillment, automation and robotics. We focus on high quality research science informed by practical problems.

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.

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.



USA, MA, BOSTON - 167,100.00 - 226,100.00 USD annually
USA, MA, Boston - 167,100.00 - 226,100.00 USD annually

Salary.com Estimation for Sr. Applied Scientist, Amazon Robotics in Boston, MA
$122,026 to $152,912
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