AWS is seeking a Robotics Engineer to support building systems that operate in our data centers and collect rich sensor data at scale. We're seeking a Generalist Machine Learning Engineer to own the ML that turns robot-collected data — imagery, LiDAR, thermal streams, etc — into useful, reliable outputs. The ideal candidate has a proven track record of reliable performance in production across a broad range of problems — perception, model fine-tuning, evaluation, and the pipelines that feed and serve them. This role closely collaborates with robotics and software engineers so model outputs are usable downstream, and so field data feeds back into better training data and better models.
As Amazon has a global presence, intermittent travel will be necessary and should be expected to be approximately 30% to AWS offices, data centers, suppliers, vendors, and product validation tests. While most travel will be domestic, some international travel may be required.
About the team
Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness.
Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Bachelor's degree or above in computer science, machine learning, engineering, or related fields
4+ years of professional software engineering experience, including shipping ML to production.
Strong general software engineering and debugging skills, and fluency in Python.
Hands-on experience owning problems across the full ML stack: data/feature pipelines, model training, evaluation, and deployment.
Hands-on experience with the AWS ML stack (or equivalent) — Amazon SageMaker AI (training, tuning, endpoints), Amazon Bedrock, S3-based data/feature pipelines, and GPU training on EC2.
Computer vision / perception experience (detection, segmentation, recognition) on real-world sensor data — RGB, PCD, etc.
Experience as the sole or lead ML engineer on a team of otherwise non-ML engineers.
Familiarity with robotics data and tooling (ROS 2, MCAP, sensor fusion) and edge deployment.
Experience fine-tuning and evaluating open models / LLMs, and building evaluation harnesses.
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 - 134,300.00 - 185,000.00 USD annually
USA, CA, Santa Clara - 134,300.00 - 185,000.00 USD annually
USA, TX, Austin - 116,800.00 - 160,000.00 USD annually
USA, WA, Seattle - 116,800.00 - 160,000.00 USD annually
