Job description

Are you curious about what happens inside the servers that power AI? Do you enjoy debugging problems and figuring out why something broke? Are you excited to learn fast, work on real systems, and see your contributions matter from day one? If that sounds like you, we'd love to meet you. AWS Hardware Engineering builds and maintains the servers behind the world's largest cloud. Our team focuses on GPU-accelerated platforms — the infrastructure that runs generative AI, machine learning training, and large language models at global scale. It's complex, it's fast-moving, and it's an incredible place to start your career. We're looking for a Hardware Development Engineer to join us and grow. You don't need to know everything on day one — you need to be curious, willing to learn, and energized by solving problems. You'll be supported by experienced engineers who'll mentor you as you ramp up on real fleet challenges: understanding why a GPU server misbehaves, building tools to catch issues automatically, and helping improve the reliability of infrastructure used by millions. You'll learn how servers work end-to-end — hardware, firmware, software, and operations — and you'll contribute to a team that's pushing toward a future where systems heal themselves. Your ideas will matter, your work will ship, and you'll develop skills that are hard to get anywhere else. Key job responsibilities - Investigate and root cause hardware issues on GPU server platforms with support of an experienced engineer — you'll learn to trace problems across electrical, firmware, and software layers - Analyze failure data and trends to identify systemic problems and propose fixes - Work with senior engineers to understand server architecture, GPU subsystems, and fleet operations - Participate in design reviews for new server platforms, contributing a reliability and serviceability perspective - Collaborate with cross-functional teams (firmware, software, manufacturing, datacenter operations) to close the loop between field failures and design improvements - Document findings, contribute to runbooks, and share knowledge with the team A day in the life - You'll work on infrastructure at a scale that doesn't exist anywhere else - You'll develop rare cross-stack expertise (hardware + firmware + software + operations) early in your career - You'll have mentorship from senior engineers and a team that invests in your growth - You'll see your work directly improve the systems powering the next generation of AI - Bachelor's degree or above in electrical engineering, computer engineering, or equivalent - Experience communicating technical concepts and processes using clear, simple language and visuals - Understanding of computer architecture (CPU, memory, buses, I/O) - Hands-on experience with Linux environments (coursework, labs, or personal projects) - Strong organizational skills and the ability to work well with cross-functional teams - Desire and energy to work in a fast-paced, learning-intensive environment - Experience programming or scripting language like Python, Java, C or C++ - co-op program at your university in engineering or equivalent, or experience from previous technical internship(s) or demonstrated project experience - 1+ years of industry work experience - Coursework or projects in embedded systems, computer architecture, or hardware-software interaction - Experience debugging hardware or software issues in lab or project settings 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. 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 amazon.jobs 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 amazon.jobs . USA, CA, Cupertino - 126,100.00 - 185,000.00 USD annually

Requirements

Must-haves

Key job responsibilities
Investigate and root cause hardware issues on GPU server platforms with support of an experienced engineer — you'll learn to trace problems across electrical, firmware, and software layers
Analyze failure data and trends to identify systemic problems and propose fixes
Work with senior engineers to understand server architecture, GPU subsystems, and fleet operations
Participate in design reviews for new server platforms, contributing a reliability and serviceability perspective
Collaborate with cross-functional teams (firmware, software, manufacturing, datacenter operations) to close the loop between field failures and design improvements
Document findings, contribute to runbooks, and share knowledge with the team
A day in the life
You'll work on infrastructure at a scale that doesn't exist anywhere else
You'll develop rare cross-stack expertise (hardware + firmware + software + operations) early in your career
You'll have mentorship from senior engineers and a team that invests in your growth
You'll see your work directly improve the systems powering the next generation of AI
Bachelor's degree or above in electrical engineering, computer engineering, or equivalent
Experience communicating technical concepts and processes using clear, simple language and visuals
Understanding of computer architecture (CPU, memory, buses, I/O)
Hands-on experience with Linux environments (coursework, labs, or personal projects)
Strong organizational skills and the ability to work well with cross-functional teams
Desire and energy to work in a fast-paced, learning-intensive environment
Experience programming or scripting language like Python, Java, C or C++
co-op program at your university in engineering or equivalent, or experience from previous technical internship(s) or demonstrated project experience
1+ years of industry work experience
Coursework or projects in embedded systems, computer architecture, or hardware-software interaction
Experience debugging hardware or software issues in lab or project settings
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Nice-to-haves

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Application prep

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Keywords to mirror

aiawsmachine learningpythonjava

Platform: amazon
Effort: medium

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401(K)

Paid Time Off

Parental Leave