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Amazon
Amazon

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Principal Applied Scientist, Robotics

직무머신러닝
경력Staff+
위치N.reading, Morocco, United States
근무오피스 출근
고용정규직
게시2주 전
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We are seeking a Principal Applied Scientist to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models.

We leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence.

The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment.

Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration.

  • Key job responsibilities
  • Define and drive the long-term scientific roadmap for whole body control and dexterous manipulation, working with autonomy and delivering artifacts that set the standard for scientific and engineering excellence
  • Serve as the primary technical authority on whole body control methods — including reinforcement learning, imitation learning, hierarchical quadratic programming, and model-predictive control — across the organization
  • Identify and tackle intrinsically hard, open-ended research problems in loco-manipulation, acquiring expertise as needed and proposing innovative solutions that span multiple teams
  • Collaborate with hardware and robotics leads to co-design systems for loco-manipulation, ensuring science solutions are grounded in real-world deployment constraints
  • Represent scientific capabilities to senior leadership and external partners; communicate complex technical concepts to both technical and non-technical audiences
  • Mentor and develop a community of Applied Scientists and engineers, raising the scientific bar across the organization

Basic Qualifications

  • PhD in Robotics, Computer Science, Mechanical Engineering, or a related field, with 7+ years of relevant research experience after degree; or Master's degree with 12+ years of equivalent experience
  • Deep expertise in whole body control methods, including hierarchical quadratic programming (HQP) and model-predictive control (MPC)
  • Proven experience with imitation learning and reinforcement learning applied to whole body control and manipulation
  • Experience developing and deploying real-time controllers on physical robotic hardware
  • Experience with simulation environments such as Isaac Lab, Mu JoCo, or Drake
  • Experience in state estimation from multiple sensor modalities
  • Demonstrated ability to influence technical strategy across multiple teams and organizations

Preferred Qualifications

  • Experience co-designing hardware and algorithms for loco-manipulation systems
  • Strong record of mentoring scientists and engineers and growing high-performing teams
  • PhD in Robotics with a focus on whole body control or dexterous manipulation
  • Track record of publications and/or patents in robotics, control, or machine learning

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, N.Reading - 198,900.00 - 269,000.00 USD annually

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Amazon 소개

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

직원 수

Seattle

본사 위치

$1.5T

기업 가치

리뷰

10개 리뷰

3.4

10개 리뷰

워라밸

2.5

보상

4.2

문화

3.0

커리어

3.8

경영진

2.7

65%

지인 추천률

장점

Great benefits and competitive pay

Learning and advancement opportunities

Good teamwork and colleagues

단점

High pressure and long hours

Poor work-life balance

Toxic work culture and management issues

연봉 정보

4개 데이터

Junior/L3

L2

L6

M3

M4

M5

M6

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

L3

L4

L5

Junior/L3 · Data Scientist L4

0개 리포트

$181,968

총 연봉

기본급

-

주식

-

보너스

-

$154,672

$209,264

면접 후기

후기 6개

난이도

4.0

/ 5

소요 기간

21-35주

경험

긍정 0%

보통 17%

부정 83%

면접 과정

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Technical Interview

6

Onsite/Virtual Interviews

자주 나오는 질문

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge