Hardware System Diagnostic Engineer
MatX · Mountain View (HQ) or Remote
CHECKED 8H AGO
Infrastructureremotesenior$160k–$600k
At a glance
Highlights
- Own end-to-end diagnostics test suite for accelerator boards and racks.
- Enable manufacturing screening and debug for rack-scale AI data center product.
- Track yield and quality metrics from manufacturing to customer deployment.
What they offer
- 4 weeks PTO + 12 company holidays + up to 3 weeks remote work
- Company-subsidized medical, dental, vision, life insurance plus HSA/FSA
- 401K with up to 5% company contribution and company-paid disability insurance
- $1500 annual professional development budget
- Onsite lunch & dinner Monday-Friday and 100% paid commute
- $50/mo flexible perk plus cell, internet and $1000 home setup reimbursement
- 100% paid mental health benefit and up to 12 weeks paid parental leave
Ideal candidate
Self-directed systems diagnostician with 7+ years owning manufacturing test for complex hardware. Thrives in fast-moving startups, bridging engineering and manufacturing partners to drive yield and product robustness.
Requirements
- 7+ years in systems diagnostics, hardware validation, or manufacturing test
- Expert in Python and C/C++ for test automation and low-level device programming
- Deep knowledge of PCIe, memory hierarchies, power management, and I/O
- Proven experience managing test relationships with ODM/JDM or CM partners
- Experienced building and scaling test automation frameworks from the ground up
- Proficient with Linux system tools for hardware interrogation and fault analysis
- Self-directed and effective in a fast-moving, low-overhead startup environment
- Strong communicator across engineering, manufacturing, and executive audiences
- remote policy
- Up to 3 weeks remote work
Lab profile
About MatX
Designs vertically integrated AI silicon and systems to run frontier models at physics-limit efficiency.
What they build
- AI accelerator silicon for GenAI training and inference
- Rack-scale AI data center systems
- Full-stack silicon-to-software platform for large ML workloads
Known for
- Vertically integrated silicon-to-systems design
- AI accelerator architecture and performance modeling for LLMs
- High-efficiency power architecture from chip to rack
- Silicon verification and software-hardware co-verification