Staff Mechanical Engineer - Data Center Cooling
Lambda· Data Center Business
Hybrid (San Francisco Office (Fremont St)), Hybrid (San Jose Office (First St))$349k - $465kFull-timePosted 1mo ago
About the role
Staff Mechanical Engineer focused on designing and standardizing cooling systems for Lambda's large-scale AI data centers, including air-cooled, liquid-cooled, and hybrid solutions, with involvement from concept through commissioning.
Responsibilities
- Own cooling-system standards and reference architectures for large-scale AI data centers.
- Design the complete thermal path from GPU and rack heat capture through facility distribution and final heat rejection.
- Translate server, rack, and cluster requirements into coolant temperature, flow, pressure, water-quality, and facility-capacity requirements.
- Develop air-cooled, liquid-cooled, and hybrid cooling architectures for greenfield, retrofit, and partner-operated facilities.
- Design central plants, technology cooling-water loops, CDUs, heat exchangers, pumps, piping, chillers, cooling towers, dry coolers, and adiabatic systems.
- Perform thermal, hydraulic, pressure-drop, heat-transfer, psychrometric, and equipment-capacity calculations.
- Evaluate system performance across site climate conditions, compute-load changes, equipment failures, and maintenance scenarios.
- Develop and review P&IDs, equipment schedules, layouts, specifications, sequence of operation, and basis-of-design documents.
- Define requirements for redundancy, thermal ride-through, failure isolation, maintainability, efficiency, and water consumption.
- Establish requirements for coolant chemistry, materials compatibility, filtration, flushing, cleanliness, leak detection, and fluid management.
- Review partner designs, vendor submittals, equipment selections, and construction documents for compliance with Lambda standards.
- Coordinate cooling interfaces across hardware engineering, electrical engineering, controls, construction, commissioning, and operations.
- Support equipment testing, construction sequencing, commissioning, cooling-system bring-up, and initial GPU loading.
- Investigate thermal events and cooling failures, incorporating lessons into future designs and operating standards.
- Travel to project sites, manufacturers, and partner facilities as needed.
Qualifications
- Have experience designing cooling systems for data centers, mission-critical facilities, central plants, or large industrial environments.
- Understand hydronic design, heat transfer, pumping, heat exchangers, chilled-water systems, and heat-rejection equipment.
- Have experience with direct-to-chip liquid cooling, CDUs, technology cooling-water loops, or other high-density cooling systems.
- Can develop and review P&IDs, equipment specifications, mechanical layouts, and engineering calculations.
- Can model system capacity, flow, pressure loss, temperature approach, and performance across varying operating conditions.
- Understand cooling-system redundancy, failure domains, thermal ride-through, maintainability, and operational risk.
- Understand the relationship between GPU behavior, rack density, coolant conditions, and facility cooling capacity.
- Can balance reliability, efficiency, water consumption, equipment cost, and delivery schedule.
- Communicate clearly across engineering, construction, operations, equipment vendors, and executive stakeholders.
- Hold a bachelor’s degree in mechanical engineering or equivalent practical experience.
Skills
Required:Cooling-system designHydronic designThermal & hydraulic calculationsP&ID developmentCross-functional collaborationCommunication to stakeholders
Nice to have:CFD / engineering tools
Benefits
- Health, dental, and vision coverage for you and your dependents
- Wellness and commuter stipends for select roles
- 401k Plan with 2% company match (USA employees)
- Flexible paid time off plan that we all actually use
Last updated Sep 17, 2026. Interested? Apply on the company site.
About Lambda
The Superintelligence Cloud
The gigawatt-scale AI GPU Cloud built for superintelligence. Featuring on-demand & reserved cloud NVIDIA HGX B200, B300, GB200, GB300 and H200 GPUs for AI training & inference.
AI trainingDeep learningGPU CloudInferenceNVIDIA GPUsliquid-ai-recruiting-targetsetter-30setter-30-2026-q1
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