Six Figure Work

Applied Scientist, Navigation

Amazon

Company websiteamazon.com (Amazon, opens in new tab)

Base salary $171,600  to $222,200

Employer-published annual base salary, USD. Advertised base range in San Francisco, CA

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  • LocationSan Francisco, CA
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (2 h ago) · observed since

About this job

Amazon is on a mission to redefine the future of automation — and we're looking for exceptional talent to help lead the way. We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments.

At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence — and we're just getting started.

As a Sr. Scientist in Robot Navigation, you will be at the forefront of this transformation — architecting and delivering navigation systems that are intelligent, safe, and scalable. You will bring deep expertise in learning-based planning and control, a strong understanding of foundation models and their application to embodied agents, and as well as have in-depth understanding of control-theoretic approaches such as model predictive control (MPC)-based trajectory planning. You will develop navigation solutions that seamlessly blend data-driven intelligence with principled control-theoretic guarantees.

Our vision is bold: to build navigation systems that allow robots to move fluidly and safely through dynamic environments — understanding context, anticipating change, and adapting in real time. You will lead research that bridges the gap between cutting-edge academic advances and production grade deployment, collaborating with world-class teams pushing the boundaries of robotic autonomy, manipulation, and human-robot interaction.

Join us in building the next generation of intelligent navigation systems that will define the future of autonomous robotics at scale.

Key job responsibilities

  • Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding
  • Lead research initiatives in computer vision, sensor fusion and 3D perception
  • Collaborate with cross-functional teams including robotics engineers, software engineers, and product managers to define and deliver perception capabilities
  • Drive end-to-end ownership of ML models — from data collection and labeling strategy to training, evaluation, and deployment
  • Mentor junior scientists and engineers; contribute to a culture of technical excellence
  • Define and track key metrics to measure perception system performance in real-world environments
  • Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents

A day in the life

  • Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment
  • Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations
  • Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team
  • Mentor team members while maintaining significant hands-on contribution to technical solutions

About the team

Our team is a group is a diverse group of scientists and engineers passionate about building intelligent machines. We value curiosity, rigor, and a bias for action. We believe in learning from failure and iterating quickly toward solutions that matter.

Basic Qualifications

  • Experience programming in Java, C++, Python or related language
  • PhD in Robotics, Computer Science, Electrical Engineering, Controls, or a related field
  • 2+ years of experience in robot navigation, motion planning, or autonomous systems
  • Deep expertise in learning-based approaches to navigation (e.g., imitation learning, reinforcement learning, neural motion planning, diffusion-based policies)
  • Strong experience with Model Predictive Control (MPC) and optimization-based planning (PyTorch, JAX, or equivalent)
  • Proven track record of translating research into deployed systems

Preferred Qualifications

  • Experience applying foundation models or large pre-trained models to robotics tasks (navigation, manipulation, or embodied AI)
  • Familiarity with world models, visual navigation, or vision-languageaction models
  • Experience with sim-to-real transfer and high-fidelity simulation environments (Isaac Sim, MuJoCo, Gazebo)
  • Knowledge of SLAM, localization, and mapping systems
  • Experience with ROS/ROS2 and real-time robotics middleware
  • Hands-on experience deploying navigation systems on physical robots in dynamic, real-world environments
  • Experience with safety-critical systems and formal verification of learned controllers
  • Familiarity with multi-agent coordination and fleet-level navigation

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.

Pursuant to the San Francisco 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.

USA, CA, SAN FRANCISCO - 171,600.00 - 222,200.00 USD annually

Source: Amazon · View original posting (opens in new tab)

Pay in context

This role's base floor ($171,600) is above 34% of the 1,502 Data & ML roles in California listed on this site; 22 others list the same floor. Their median floor is $189,000; the middle half runs from $159,256 to $229,900.

Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 6, 2026.

This range next to 6 other live Amazon roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live Amazon roles with the nearest advertised base floor
RolePublished base
Applied Scientist, Navigation (this listing)$171,600 - $222,200
Applied Scientist, Amazon Ads$171,600 - $222,200
Applied Scientist, Fauna Robotics$171,600 - $222,200
Postdoctoral Researcher – Visual Localization & Navigation | Amazon Last Mile$171,600 - $222,200
Applied Scientist II, Kiro Science$171,600 - $222,200
Applied Scientist, Center for Quantum Computing, Physical Design and Simulation$171,600 - $222,200
Applied Scientist, AWS Agentic AI$171,600 - $222,200

Same $100K to $400K scale as every card. All Amazon roles · How to read the bar

Observed changes

  1. Began meeting the published-salary criteria
  2. First observed on the employer's board
Observed since
Employer-stated posting date
2026-05-07
Where this pay comes from

Location as the employer wrote it: US, CA, San Francisco

USA, CA, SAN FRANCISCO - 171,600.00 - 222,200.00 USD annually

Method
Employer text, read with fixed rules and re-verified
Checked
Rule set
us-base-v2

The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.