Datacenter Robotics Engineer, Datacenter Robotic Products & Services

About the role

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensures our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain - and we're looking for talented people who want to help.

You'll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

Within AIS, the DC Robotics team is growing in maturity, so now is the time to join and drive game changing and rapid innovation used by AWS globally. Our designs will fundamentally change the data center, providing operational and financial benefits that are critical to the success of the AWS business and its millions of customers.

Our engineers solve challenging technology problems and take big bets on new concepts, enabling AWS services to continue to revolutionize the industry. This role provides the opportunity to be a technical lead driving the innovations being developed and deployed in the next generation data centers.

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.

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.

Basic Qualifications

• 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.

Preferred Qualifications

• 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.

Additional information

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Pay and benefits

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.

• 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