Drimva

Amazon

Quality & Reliability Engineer, Trainium Manufacturing, Quality & Reliability

$136K–$213K

Austin, TX +1 · Full-time · Posted Apr 30, 2026

Location
Austin, TX
Cupertino, CA
Experience
7+ years of reliability engineering work experience with server compute platforms or high-tech hardware; alternatively, 2+ years of maintenance or engineering experience for the education requirement.
Education
Bachelor's degree in Electrical or Mechanical Engineering, Engineering Technology, or Reliability Engineering, or equivalent experience as specified: 2+ years of maintenance or engineering experience.

About the job

Defines and validates reliability tests for Trainium manufacturing, improves manufacturing processes, predicts product and component failure mechanisms, and works with design teams, vendors, and ODMs to ensure product reliability.

What you'll do

  • Define and implement reliability tests during manufacturing; identify product and component risks and establish test coverage.
  • Improve manufacturing processes and perform reliability predictions for products in development and in the field.
  • Standardize component manufacturing and reliability expectations with vendors and ODMs; provide technical leadership and mentor engineers.

What they ask for

  • Bachelor's degree in Electrical or Mechanical Engineering, Engineering Technology, or Reliability Engineering, or 2+ years of maintenance or engineering experience.
  • 7+ years of reliability engineering work experience with server compute platforms or high-tech hardware.

Nice to have

  • Reliability modeling and materials characterization experience.
  • Analytical, test plan, and test procedure development experience related to server compute platforms or high-tech hardware.

Pay

157,300.00 - 212,800.00 USD annually (base salary); 136,000.00 - 184,000.00 USD annually (base salary)

Tools

Trainium, Nitro, Graviton, Inferentia, CPU, GPU, HDD, SSD

AI focus

Reliability engineering for Trainium machine-learning hardware and manufacturing; defines tests and predicts failure mechanisms for products and components.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 5, 2026 (UTC)