Qualcomm
Sr. Staff Hardware Design Engineer, AI Accelerators
$170K–$255K
Austin, Texas +2 · On-site · Senior Staff · Full-time · Posted Oct 27, 2026
- Location
- Austin, Texas
San Diego, California
Santa Clara, California - Experience
- Bachelor's degree: 6+ years; master's degree: 5+ years; PhD: 4+ years of Hardware Engineering or related work experience. Preferred: 10+ years hardware engineering/systems development experience; also lists 4+ years in several specialty areas.
- Education
- Bachelor's, master's, or PhD in Computer Science, Electrical/Electronics Engineering, Engineering, or a related field.
About the job
Designs and develops board-, card-, module-, and rack-level hardware for Qualcomm AI inference systems, from architecture and validation through production and deployment.
What you'll do
- Lead schematics, PCB layouts, component selection, design reviews, test planning, and hardware bring-up and debugging.
- Coordinate system integration and hardware development with cross-functional teams, ODMs, and manufacturing partners.
- Develop rack-level inference solutions and resolve technical issues across system, card, and rack designs.
What they ask for
- Experience with system-, card-, or rack-level enterprise hardware development, including architecture, design, validation, and deployment.
- Proven rack-level integration experience spanning mechanical, thermal, power, diagnostics, and manufacturing collaboration.
- Hands-on experience designing and debugging dense, high-layer-count PCBs and PCIe cards or modules; familiarity with JTAG bring-up.
- Knowledge of high-speed interfaces and signal integrity, with proficiency in schematic/PCB design tools and circuit simulation.
Nice to have
- Master's degree in Electrical and Electronic Engineering, Computer Engineering, or a related field.
- 10+ years of hardware engineering/systems development experience; 4+ years in circuit design, schematic capture and simulation, or hardware measurement instruments.
Pay
$169,800.00 - $254,600.00 USD base salary
Tools
PCIe Gen5/6, LPDDR4x/5x, DDR4/5, 200/400/800 GbE, Cadence Allegro, Mentor Expedition, SPICE, JTAG
AI focus
Design and development of rack-level AI inference hardware and systems.
Model-written summary · the original posting is authoritative