GPU Performance Engineer - Production Inference & Systems

Gimlet Labs, Inc.; San Francisco (CA); On-site; USD 180,000 - 300,000; Full time

Job summary

Gimlet Labs, Inc. is seeking a Member of Technical Staff to 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, tying hardware signals to end‑to‑end latency and throughput. This role involves building measurement systems and methodologies to quickly evaluate new accelerators and drive

Qualifications

• Must have strong software engineering fundamentals and performance-critical systems experience.
• Experience profiling GPU/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.

Responsibilities

• 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, and runtime scheduling; use profiling and models to explain data.
• Improve execution through launch reduction, graph capture, stream coordination, and memory reuse; build automated benchmarks and regression tests.
• Translate performance findings into production improvements with kernel, compiler, ML systems, and distributed systems engineers where needed.
• Develop a repeatable methodology for evaluating and bringing up new accelerators within Gimlet's execution platform.

Skills

Software engineering fundamentals

GPU/accelerator profiling

GPU memory hierarchies

Experiment design

Education

Bachelor's degree in a relevant field

Tools

Nsight Systems

Nsight Compute

rocprof

Omniperf

VTune

Perfetto

CUDA

HIP

Triton

Job description

Gimlet Labs, Inc. is seeking a Member of Technical Staff to 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, tying hardware signals to end‑to‑end latency and throughput. This role involves building measurement systems and methodologies to quickly evaluate new accelerators and drive