AmazonApplied Science Manager, Fleet Autonomy, Amazon Robotics
Amazon is hiring an Applied Science Manager, Fleet Autonomy, Amazon Robotics. It pays $184k-$249k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- The posting mentions computer vision, robotics and fleet management among its tools and skills.
- Level classes it as a lead role.
- Amazon has 20,000+ other open roles on Level.
AI in this role
Lead an applied science team inventing autonomous mobile robot coordination and fleet behavior algorithms for Amazon Robotics.
Proteus is Amazon's first fully autonomous mobile robot and navigates freely alongside people in our fulfillment centers, perceiving its environment and making decisions in real time. The fleet is growing quickly in scale, diversity, and intelligence, with thousands of robots deployed and new platforms including mobile manipulation entering the mix. The science challenge is making a diverse, heterogeneous fleet perform reliably in a world that changes constantly — where priorities shift hour to hour, new capabilities come online, and operational conditions create new constraints.
Your team will own algorithms at multiple layers of this system: how groups of robots autonomously coordinate through intersections and corridors, how fleet traffic is shaped across the road network, which tasks are assigned to which robots and when, and a new fleet orchestration layer that interacts directly with Operations to take in requests, collaborate to solve complex operational challenges, and adapt fleet performance and behavior on the fly.
Whether you've been leading a research team in industry and want a bigger canvas, or you've been driving impactful academic research in close partnership with industry and are ready to make the leap, this is a role where your ideas become fleets of robots, and those robots deliver for hundreds of millions of customers.
Key job responsibilities
• Set the technical vision and research agenda; identify the right problems and sequence bets across near-term production needs and long-horizon research
• Build, hire, and develop a team of applied scientists; provide scientific mentorship and grow careers
• Drive algorithms from research through production deployment in partnership with engineering
• Represent the team externally through publications, academic collaborations, and community engagement
A day in the life
Your internal stakeholders are engineering teams who productionize your algorithms, operations leaders whose buildings depend on fleet performance, and peer scientists building learned models of fleet dynamics. You spend your time shaping research direction, unblocking technical challenges, reviewing experimental results, and partnering across disciplines to get science into production.
About the team
You would join a multi-disciplinary science organization with deep expertise in planning, optimization, machine learning, and robotics — working at the frontier of multi-robot coordination where scale, diversity, and dynamism intersect. Our algorithms ship to real robots within months of conception, and we learn from the operational data they generate. We maintain active academic collaborations and contribute to the research community through publications, workshops, and open problems.
Basic qualifications
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- 5+ years of industry or academic research experience
- 2+ years of scientists or machine learning engineers management experience
- Experience programming in Java, C++, Python or related language
- Experience building machine learning models or developing algorithms for business application
- Strong understanding of autonomous mobile robots and how they navigate
- Experience deploying robotic systems into the field
Preferred qualifications
- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
- Experience with mobile robot fleets in industrial or logistics settings
- Experience developing computationally efficient decision making algorithms for live production systems
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 - 183,800.00 - 248,700.00 USD annually
How we rate this
Applied Science Manager, Fleet Autonomy, Amazon Robotics at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- Tell me about a project where robotics was part of your work. What did you do?
- Tell me about a project where fleet management was part of your work. What did you do?
- Tell me about a project where algorithms was part of your work. What did you do?
- Tell me about a project where applied science was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Computer vision, Robotics, Fleet Management, Algorithms, and Applied Science. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
Get your CV reviewed before you apply
Send your CV and the role you want next. Your review arrives by email within 3 days.
Get new AI jobs (Builds AI ●●●●) by email
One email a week, each job rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free.
Similar roles
Other roles that build AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step