Staff Mechanical Engineer - Data Center Cooling
Lambda Labs · San Francisco Office (Fremont St) · San Jose Office (First St)
Infrastructureremotestaff$349k–$465k
At a glance
Highlights
- Own cooling standards for large-scale AI data centers end to end.
- Design full thermal path from GPU heat capture to heat rejection.
- Lead cooling bring-up and initial GPU loading at live sites.
What they offer
- Generous cash and equity compensation
- Health, dental, and vision coverage for you and dependents
- Wellness and commuter stipends for select roles
- 401(k) plan with 2% company match
- Flexible paid time off plan
Ideal candidate
Mechanical engineer who thrives owning complex cooling systems end-to-end, balancing reliability, efficiency, and delivery to power large-scale AI infrastructure.
Requirements
- Experience designing cooling systems for data centers, mission-critical facilities, central plants, or large industrial environments
- Understanding of hydronic design, heat transfer, pumping, heat exchangers, chilled-water systems, and heat-rejection equipment
- Experience with direct-to-chip liquid cooling, CDUs, technology cooling-water loops, or high-density cooling systems
- Ability to develop and review P&IDs, equipment specifications, mechanical layouts, and engineering calculations
- Ability to model system capacity, flow, pressure loss, temperature approach, and performance
- Understanding of cooling-system redundancy, failure domains, thermal ride-through, and maintainability
- Understanding of relationship between GPU behavior, rack density, coolant conditions, and facility cooling capacity
- Clear communication across engineering, construction, operations, vendors, and executive stakeholders
- Bachelor's degree in mechanical engineering or equivalent practical experience
- remote policy
- 4 days in office per week, work from home on Tuesdays
Lab profile
About Lambda Labs
The Superintelligence Cloud delivering GPU compute infrastructure for AI researchers and enterprises.
What they build
- GPU cloud infrastructure
- On-demand GPU instances
- Managed Kubernetes for AI workloads
Known for
- AI cloud infrastructure at scale
- HPC platform and hardware engineering
- Data center operations and networking
Key facts
- Serves tens of thousands of customers
- Offices in San Francisco, San Jose and Bellevue
- Data center in Quebec City, Canada
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