Onsite IT Support
MatX · Mountain View (HQ) or Remote
CHECKED 9H AGO
Infrastructureremotemid-level$44k–$76k
At a glance
Highlights
- Be the first point of contact for IT support for 100+ users.
- Keep office technical infrastructure and conference rooms running.
- Help make the world's best AI models run as efficiently as physics allows.
What they offer
- 3-month fixed-term contract with conversion review to full-time employment
- 4 weeks PTO plus 12 company holidays and up to 3 weeks remote work
- Company-subsidized medical, dental, vision and life insurance plus HSA/FSA
- 401K with up to 5% company contribution and company-paid disability insurance
- $1500 annual professional development budget
- Onsite lunch and dinner Monday-Friday plus 100% paid commute
- Up to 12 weeks paid parental leave and mental health benefits via SpringHealth
Ideal candidate
Organized, self-starting IT support pro with 2-4 years in fast-paced environments who thrives on helping people, staying calm as priorities shift, and keeping systems running smoothly.
Requirements
- 2-4 years of experience in IT support, help desk, or similar role
- Experience with Google Workspace administration, GitHub, and Linux
- Basic networking and security knowledge
- Highly organized, detail-oriented with clear written and verbal communication
- Able to learn new tools quickly and stay effective as priorities shift
- Based in or willing to relocate to San Francisco Bay Area and work on-site in Mountain View 3 days per week
- Able to handle sensitive and confidential information with discretion
- remote policy
- At least 3 days per week on-site in Mountain View
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