
51 - 200 employees
🤖 Artificial Intelligence
🔧 Hardware
☁️ SaaS
🔥 Funding within the last year
💰 $300M Series B on 2026-09
Artificial Intelligence • Hardware • SaaS
Gimlet Labs is an applied research lab building the next generation of AI systems and infrastructure. They develop a serverless inference platform (Gimlet Cloud) for running agentic and multi-stage AI workloads, and kforge, a system that autonomously generates optimized low-level kernels from PyTorch for heterogeneous hardware (CUDA, ROCm, Metal). Their research covers AI compilers, SLA-aware datacenter scheduling, hybrid edge/cloud partitioning, headless hardware architectures for inference, and cost-aware optimization frameworks for AI workloads. Gimlet focuses on making AI workloads portable, performant, and cost-efficient across diverse hardware and deployment environments.
🔥 2 minutes ago
Where this job comes from
Posted on Gimlet Labs's careers page, not through a job board
First seen by Remote Rocketship 2 minutes ago

51 - 200 employees
🤖 Artificial Intelligence
🔧 Hardware
☁️ SaaS
🔥 Funding within the last year
💰 $300M Series B on 2026-09
Artificial Intelligence • Hardware • SaaS
Gimlet Labs is an applied research lab building the next generation of AI systems and infrastructure. They develop a serverless inference platform (Gimlet Cloud) for running agentic and multi-stage AI workloads, and kforge, a system that autonomously generates optimized low-level kernels from PyTorch for heterogeneous hardware (CUDA, ROCm, Metal). Their research covers AI compilers, SLA-aware datacenter scheduling, hybrid edge/cloud partitioning, headless hardware architectures for inference, and cost-aware optimization frameworks for AI workloads. Gimlet focuses on making AI workloads portable, performant, and cost-efficient across diverse hardware and deployment environments.
• Build the facilities operations model for current and future Gimlet sites, including operating standards, escalation paths, maintenance routines, acceptance criteria, and facility readiness gates • Translate OEM and engineering requirements for liquid-cooled platforms into practical site operating envelopes for temperature, flow, pressure, water quality, alarms, and heat rejection • Own monitoring and response for facility-side telemetry, including supply and return water temperatures, delta-T, flow, pressure, leak detection, CDU status, cooling capacity margins, and BMS/DCIM alarms • Partner with colocation providers, facility vendors, OEMs, Site Managers, Data Center Technicians, Deployment Leads, and TPMs to ensure facilities are ready before new compute capacity is deployed • Create and maintain MOPs, SOPs, EOPs, maintenance windows, runbooks, inspection routines, and incident response procedures for critical facilities and liquid cooling operations • Coordinate preventive maintenance, repairs, and vendor response for CDUs, facility water loops, filters, valves, pumps, sensors, leak detection systems, chillers, dry coolers, CRAHs, and related infrastructure • Lead facility-side root cause analysis for thermal, leak, power, cooling, monitoring, and environmental events, then drive durable corrective actions • Build reporting that shows facility health, risk, readiness, capacity margin, recurring issues, open repairs, and operational trends across Gimlet sites • Support Gimlet's production neocloud expansion across new hardware, customers, and data centers
• Experience in data center facilities operations, critical facilities engineering, MEP operations, commissioning, or facilities maintenance • Experience operating liquid-cooled, high-density compute infrastructure • Familiarity with facility water systems, CDUs, heat rejection, leak detection, and water-quality controls • Experience using BMS, DCIM, EPMS, or similar systems to monitor and respond to facility conditions • Ability to create and execute operational procedures with strong attention to safety and reliability • Experience coordinating across site teams, colocation providers, OEMs, and facilities vendors • Ability to work in active data center environments and support urgent facilities escalations • Experience supporting GPU, HPC, or rack-scale liquid-cooled infrastructure may be advantageous • Experience with commissioning, integrated systems testing, site acceptance, or facility turnover may be advantageous • Familiarity with power distribution, UPS and generator systems, chilled water, dry coolers, CRAH/CRAC systems, or rear-door heat exchangers may be advantageous • Experience managing colocation obligations, service levels, maintenance windows, and vendor escalations may be advantageous • Track record of improving facility reliability through monitoring, preventive maintenance, and incident analysis may be advantageous
• Equity • Work-from-home/remote work arrangement
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