Robotics Hardware Engineer, Data Center Robotics

Amazon is hiring a Robotics Hardware Engineer, Data Center Robotics in Austin, United States. It pays $134k-$185k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

Little AI ●○○○ is how Level rates this role: aI is not part of the work.
Level classes it as a senior role.
Amazon has 20,000+ other open roles on Level.
Posted in the last few days.

AI in this 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 driving game changing and rapid innovation used by AWS globally. Our products will fundamentally change our data centers, providing operational efficiencies and financial benefits that are critical to the success of AWS 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 Hardware Engineer to design, prototype, and bring to production the mechanical and thermal systems that enable robots to operate reliably in our data centers. You will own hardware from early-stage concept sketches and CAD models through FEA/CFD validation, prototype builds, manufacturing engagement, and production ramp. The ideal candidate is equally comfortable running a CFD simulation on a cooling manifold as they are on the shop floor reviewing first articles with a supplier. This role closely collaborates with robotics software engineers, electrical engineers, and ML engineers to ensure that mechanical designs meet sensor mounting requirements, thermal budgets, serviceability targets, and the harsh realities of a data center environment. You will be the bridge between design intent and manufactured reality — championing DFM/DFA throughout the development cycle and driving continuous improvement once hardware is in the field.

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.

Key job responsibilities
* Lead the effective and efficient delivery of engineering efforts from product development through design, test and validation, to at scale deployment
* Apply demonstrated analytical and quantitative skills; use hard data and metrics to back up assumptions and develop business cases
* Effectively interact and collaborate with customers, project sponsors, engineers, and multiple internal teams to define and deliver complex solutions
* Proactively recognize and drive opportunities to simplify processes
* Drive effective teamwork, communication, collaboration, and commitment across multiple disparate groups with competing priorities
* Anticipate bottlenecks, provide escalation management, make trade-offs, and balance business needs with technical constraints
* Identify, assess, track, and mitigate issues and risks at multiple levels
* Create, maintain, and disseminate program information to stakeholders

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 (gender diversity) 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 in Mechanical Engineering, Aerospace Engineering, Manufacturing Engineering, or an equivalent field
- 5+ years of hardware engineering experience
- Experience with CAD modelling software, such as Solidworks or MATLAB
- Experience with prototyping and implementation

Preferred qualifications

- 4+ years of industrial or commercial engineering in mission critical facilities including but not limited to: data centers, power generation or oil and gas facilities experience
- Experience carrying design concepts through exploration, development, and into deployment or mass production
- Experience with robotics work cells and their control systems, or experience working with electrical and mechanical conveyance systems
- Experience in product validation (Shock/Drop, cycle testing, environmental testing)
- Experience designing liquid cooling systems or thermal management hardware — cold plates, manifolds, quick-disconnect fittings, coolant loop routing, and leak-mitigation strategies
- Experience with structural/force analysis (FEA) and computational fluid dynamics (CFD) to validate designs prior to prototyping
- Demonstrated experience working directly with contract manufacturers and internal manufacturing teams on design for manufacturability (DFM), design for assembly (DFA), and tolerance analysis

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

How we rate this

Robotics Hardware Engineer, Data Center Robotics at Amazon rates 36 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● 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.