Senior Cloud AI Hardware Engineer - GPU/ML Servers

Amazon; Cupertino (CA); On-site; USD 183,000 - 248,000; Full time

Job summary

Amazon seeks a Sr Cloud Hardware Dev Engineer to define server architectures for AI training and inference at scale. You will lead ODM/JDM partners through development, bring-up, and production, owning fleet quality and driving improvements based on data.

The role spans thermal, mechanical, power, and signal integrity across GPU platforms. You will collaborate with firmware, software, and operations teams to deliver scalable, deployable hardware for AWS AI/ML workloads.

Qualifications

• Bachelor's degree in electrical engineering, computer engineering, or equivalent.
• Experience in developing functional specs, design verification plans, and test procedures.
• 7+ years of hardware design and development for server compute or large-scale infra.
• Experience with thermal/mechanical design, power delivery, high-speed signal integrity, or accelerator subsystems.

Responsibilities

• Define server architectures for AI training and inference at scale.
• Lead ODM/JDM partners through development and production milestones.
• Own fleet quality metrics and drive design improvements from data.
• Collaborate with firmware, software, and operations teams to ensure debuggable, serviceable designs.

Skills

Functional specifications

Design verification plans

Full product lifecycle

Thermal/Mechanical design

Power delivery

High-speed signaling

ODM/JDM collaboration

Fleet quality metrics

Education

Bachelor's degree in Electrical/Computer Engineering or equivalent

Master's degree or PhD in Electrical/Computer Engineering or related

Job description

Amazon seeks a Sr Cloud Hardware Dev Engineer to define server architectures for AI training and inference at scale. You will lead ODM/JDM partners through development, bring-up, and production, owning fleet quality and driving improvements based on data.

The role spans thermal, mechanical, power, and signal integrity across GPU platforms. You will collaborate with firmware, software, and operations teams to deliver scalable, deployable hardware for AWS AI/ML workloads.