Amazon
Hardware Engineer - ML Acceleration, Annapurna Labs
$154K–$247K
Austin, TX +1 · Full-time · Posted Apr 24, 2026
- Location
- Austin, TX
Cupertino, CA - Education
- Bachelor's degree in Electrical Engineering or a related field; a Master's degree in Electrical or Communications Engineering or a related field is preferred.
About the job
Defines, designs, and validates next-generation AWS machine-learning chips, cards, and server integrations, including PCIe and SerDes design and optimization for data-center deployments.
What you'll do
- Design and validate ML chips, cards, and server integration.
- Lead PCIe and SerDes design and execution.
- Optimize hardware for large-scale server deployments, including product performance, quality, and cost.
What they ask for
- Bachelor's degree in Electrical Engineering or a related field.
- Experience identifying bugs in architecture, algorithms, functionality, and performance, with strong debugging skills.
- Experience verifying logic at multiple levels, from IP blocks and SoCs to full-system testing.
Nice to have
- Master's degree in Electrical or Communications Engineering or a related field.
- Experience with formal verification; ARM and DSP ISAs; RF standards; or Python or Perl automation tools.
Pay
176,600.00 - 247,300.00 USD annually (base salary); 153,600.00 - 215,000.00 USD annually (base salary)
Tools
PCIe, Serdes, ARM, DSP ISAs, Python, Perl, 4G/5G NR, 802.11ad
AI focus
Design and optimize hardware for machine-learning acceleration, including next-generation ML chips and data-center deployments.
Model-written summary · the original posting is authoritative