L

Lambda

Cloud-based GPU services for AI training

Senior Mechanical Controls Engineer

Controls & Automation EngineeringConfirmed live in the last 24 hours
Full-timeHybrid

About the Job

Requirements

  • Experience designing or commissioning mechanical controls for data centers, mission-critical facilities, central plants, or industrial environments.
  • Understanding of chilled-water, condenser-water, heat-rejection, air-cooling, and liquid-cooling systems.
  • Ability to develop and review sequences of operation, P&IDs, control diagrams, wiring diagrams, points lists, and functional test procedures.
  • Understanding of PLC, DDC, and BMS architectures and protocols such as BACnet, Modbus, and OPC UA.
  • Experience with instrumentation, sensor selection, control loops, alarms, interlocks, and equipment safeties.
  • Understanding of how mechanical systems respond during equipment failures, power events, and changing thermal loads.
  • Ability to translate operational requirements into clear, testable control behavior.
  • Bachelor’s degree in mechanical, electrical, controls, or systems engineering, or equivalent practical experience.

Responsibilities

  • Own controls standards and reference architectures for mechanical systems supporting large-scale AI data centers.
  • Develop control narratives, sequences of operation, points lists, alarm matrices, cause-and-effect diagrams, and controller requirements.
  • Define automation for central cooling plants, heat-rejection systems, pumps, heat exchangers, CRAHs, CDUs, liquid-cooling loops, valves, and associated equipment.
  • Design system behavior for startup, shutdown, maintenance, component failure, utility loss, and recovery.
  • Establish requirements for sensors, actuators, meters, control panels, PLCs, DDC controllers, gateways, and operator interfaces.
  • Define BMS integration, mechanical telemetry, trending, alarming, data retention, and interfaces with other operational systems.
  • Review partner designs, vendor submittals, control drawings, network architectures, and equipment packages for compliance with Lambda standards.
  • Coordinate controls requirements across mechanical, electrical, network, hardware, construction, commissioning, and operations teams.
  • Support factory testing, site acceptance testing, commissioning, integrated systems testing, and cooling-system bring-up.
  • Troubleshoot control-loop instability, sensor errors, communication failures, nuisance alarms, and sequence deficiencies.
  • Incorporate commissioning results and operating lessons into future designs and control standards.
  • Travel to project sites, manufacturers, and partner facilities as needed.

Desired Qualifications

  • Experience with hyperscale, colocation, HPC, or AI data centers.
  • Experience controlling high-density liquid-cooling systems, CDUs, or warm-water cooling loops.
  • Familiarity with platforms from Siemens, Schneider Electric, Johnson Controls, Honeywell, Rockwell, or Tridium.
  • Experience with OT networking, controls cybersecurity, controller redundancy, or high-availability automation.
  • Familiarity with EPMS design, electrical systems SOOs, and monitoring.
  • Experience with factory acceptance testing, integrated systems testing, and live facility bring-up.
  • Familiarity with ASHRAE, ISA, and data center controls standards.
  • Experience using trend data or analytics to diagnose and optimize mechanical-system performance.

About the Company

Lambda

Cloud-based GPU services for AI training

Lambda Labs provides cloud-based GPU services for AI training and inference via its AI Developer Cloud, powered by NVIDIA GH200 Grace Hopper hardware to efficiently train large language models and generative AI. Customers access on-demand or reserved GPUs and are billed by the hour (for example, NVIDIA H100 at about $1.99/hour); it also offers Lambda Echelon, where clients own infrastructure but pay a monthly hosting and support fee, and Lambda Stack, a software suite that helps ML teams install and upgrade tools like PyTorch, TensorFlow, CUDA, cuDNN, and NVIDIA drivers. The company differentiates itself through competitive pricing, available high-end hardware, and an integrated ML software stack that streamlines workflows. Its goal is to enable scalable, affordable AI development and deployment by providing flexible GPU access, reliable hosting, and easy software deployment for teams working with large models.

Company size
501-1,000
Company stage
Late Stage VC
Total funding
$9.1B
Headquarters
San Jose, CA
Founded
2012

Recently Posted Jobs

Explore more opportunities at Lambda

See more jobs