--- title: Member Technical Staff GPU Performance at Gimlet Labs description: Gimlet Labs is hiring for the Member Technical Staff GPU Performance role in San Francisco, CA. See the full description and apply. type: job url: https://www.foundrole.com/jobs/member-technical-staff-gpu-performance-at-gimlet-labs-01a17971-287c-7635-8582-f1feb19ab4bb date: 2026-11-15T01:26:44Z og_description: Join Gimlet Labs as Member Technical Staff GPU Performance in San Francisco, CA. Pays $150K–$390K per year. Full-time, on-site role. og_image: https://www.foundrole.com/og/q39swl.png breadcrumbs: - label: Home url: https://www.foundrole.com/ - label: Search url: https://www.foundrole.com/jobs --- | | | |---|---| | **Company** | Gimlet Labs | | **Location** | San Francisco, CA | | **Salary** | $150K/yr - $390K/yr | | **Type** | Full Time | | **Posted** | Oct 26, 2026 | ## Is this job real? **Ghost job check:** A- · Low risk. Probably a real opening. ## Visa sponsorship - **H-1B:** Gimlet Labs sponsors H-1B visas. It filed 7 H-1B petitions (FY2026 Q1 – FY2026 Q4). - **E-Verify:** Gimlet Labs uses E-Verify. ## Pay for similar jobs Most similar jobs pay $188,000 – $262,000 a year (median $222,000). ## Description **About us** Gimlet is building the first multi-silicon neocloud designed for fast, efficient AI inference. We combine large-scale compute infrastructure with an execution platform that partitions AI workloads and maps each stage to the hardware best suited to run it. We work with foundation labs, hyperscalers, and AI-native companies, giving our team access to technical problems spanning frontier models, production infrastructure, and emerging hardware. **About the role** As a Member of Technical Staff, you will characterize and improve the performance of production AI inference across Gimlet's heterogeneous accelerator fleet. You will work across kernel execution, compiler output, runtime behavior, memory movement, synchronization, scheduling, and multi-device execution. Rather than treating performance as a collection of isolated microbenchmarks, you will connect hardware-level evidence to end-to-end latency, throughput, utilization, and cost. You will build the measurement systems and performance methodology that let Gimlet understand new hardware quickly, identify the limiting resource in real workloads, and turn that understanding into changes across kernels, compilers, runtimes, and distributed execution. **What success looks like** In the first 12-18 months, you will: - Establish trustworthy performance baselines for production inference workloads across established and emerging accelerator architectures - Isolate bottlenecks across compute, memory bandwidth, cache behavior, kernel launch, synchronization, host-device interaction, communication, and runtime scheduling ● Use profiling, hardware counters, controlled experiments, and performance models to explain why a workload behaves as it does and identify the highest-leverage optimization - Improve execution through changes such as launch reduction, graph capture, stream and event coordination, compute-communication overlap, memory reuse, batching, and scheduling ● Build automated benchmarks and regression detection that preserve performance across models, tensor shapes, data types, software releases, and hardware targets - Translate performance findings into production improvements, partnering with kernel, compiler, ML systems, and distributed systems engineers when necessary - Develop a repeatable methodology for evaluating and bringing up new accelerators within Gimlet's execution platform **You may be a good fit if you have** - Strong software engineering fundamentals and experience working on performance-critical systems - Experience profiling GPU or accelerator workloads and turning measurements into production improvements - A strong understanding of GPU execution, memory hierarchies, asynchronous execution, synchronization, and performance tradeoffs - The ability to design controlled experiments, distinguish symptoms from root causes, and communicate performance findings precisely - Bachelor's degree in a relevant field, or an equivalent combination of education, training, and professional experience **Strong candidates may also have** - Experience with Nsight Systems, Nsight Compute, rocprof, Omniperf, VTune, Perfetto, or hardware performance counters - Experience with CUDA, HIP, Triton, or another accelerator programming model and the ability to prototype low-level optimizations - Familiarity with roofline analysis, queueing behavior, occupancy, latency hiding, instruction throughput, and memory-bandwidth analysis - Experience optimizing inference runtimes, execution graphs, memory allocators, kernel dispatch, batching, or model-serving systems - Familiarity with collective communication, topology-aware execution, and compute-communication overlap across multiple accelerators - Experience building performance laboratories, benchmark suites, regression infrastructure, or hardware bring-up methodology **Why join now?** Gimlet is expanding from its core technology into a production neocloud spanning new hardware, customers, and data centers. - Solve hard problems. - Own meaningful work. - Build for production. - Help define what’s next. *Agency Policy:* *Gimlet Labs does not accept unsolicited resumes from recruitment agencies or search firms. Any unsolicited resumes submitted without a signed agreement will be considered the property of Gimlet Labs, and no fees will be paid.* ## Skills - NVIDIA Triton Inference Server - Caching - Event Coordination - Controlled Experiments - Linux Kernel Development - NVIDIA Nsight Systems - Intel VTune Profiler - CNC Turning - Compiler Design - Regression Analysis - Hardware Bring-up - High-Performance Building Design - GPU (Graphics Processing Unit) - NVIDIA Nsight - NVIDIA CUDA - Queueing Theory - Communication - Machine Learning - Model Serving - Distributed Systems ## Related - [Technology & Software jobs](https://www.foundrole.com/careers/technology-and-software?utm_source=ai_markdown)- [Software Development jobs](https://www.foundrole.com/careers/technology-and-software/software-development?utm_source=ai_markdown)- [Software Developer / Engineer jobs](https://www.foundrole.com/careers/technology-and-software/software-development/software-developer-engineer?utm_source=ai_markdown)- [Performance Engineer jobs](https://www.foundrole.com/careers/technology-and-software/software-development/software-developer-engineer/performance-engineer?utm_source=ai_markdown)- [Browse all companies](https://www.foundrole.com/companies?utm_source=ai_markdown) ## Explore this job market - [California](https://www.foundrole.com/locations/us/california?utm_source=ai_markdown) — 260758 jobs - [San Francisco, CA](https://www.foundrole.com/locations/us/california/san-francisco?utm_source=ai_markdown) — 27903 jobs - [Data Infrastructure and Analytics](https://www.foundrole.com/sectors/technology/data-infrastructure-and-analytics?utm_source=ai_markdown) — 15448 jobs ## Related pages - [California](https://www.foundrole.com/locations/us/california?utm_source=ai_markdown) — 260758 jobs - [San Francisco, CA](https://www.foundrole.com/locations/us/california/san-francisco?utm_source=ai_markdown) — 27903 jobs - [Data Infrastructure and Analytics](https://www.foundrole.com/sectors/technology/data-infrastructure-and-analytics?utm_source=ai_markdown) — 15448 jobs ## Browse - [Companies](https://www.foundrole.com/companies?utm_source=ai_markdown) - [Jobs by country](https://www.foundrole.com/locations?utm_source=ai_markdown) - [Jobs in the United States by state and city](https://www.foundrole.com/locations/us?utm_source=ai_markdown) - [H1B sponsors by location](https://www.foundrole.com/h1b-sponsors?utm_source=ai_markdown) - [H1B salaries](https://www.foundrole.com/h1b-salaries?utm_source=ai_markdown) - [Sectors and industries](https://www.foundrole.com/sectors?utm_source=ai_markdown) - [Jobs by career field](https://www.foundrole.com/careers?utm_source=ai_markdown) - [Latest jobs](https://www.foundrole.com/jobs/latest?utm_source=ai_markdown)