Hardware Development Engineer, AI/ML Server Development

Application deadline: Jul 28, 2026

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