Senior External GPU & ASIC Performance Modeling Engineer

General Diffusion, Inc.; San Francisco, Northern (CA, KY); Hybrid; USD 180,000 - 290,000; Full time

Job summary

General Diffusion, Inc. in San Francisco seeks a Member of Technical Staff to develop portable measurements and predictive performance models for external GPUs and ASICs, covering compute, memory, data movement, and contention.

You will produce traceable, evidence-backed capability profiles for compute-world-model, compiler, and runtime partners. The role emphasizes calibrating models to measurements, designing repeatable experiments, and collaborating with GPU Systems & Fabric on multi-device

Qualifications

• Experience in accelerator architecture or performance modeling grounded in measured GPU, inference-ASIC, or comparable heterogeneous-system behavior.
• Ability to design benchmarks that combine focused microkernels with representative workloads, control confounding variables, and make results reproducible.
• Demonstrated model-to-measurement correlation work, including calibration, error analysis, and clear treatment of uncertainty under workload or architecture shift.
• Fluency with performance-profiling methods and the interaction of arithmetic intensity, memory hierarchy, occupancy or utilization, and data movement.
• Vendor-neutral hardware–software judgment: able to compare capabilities through evidence rather than feature lists, and communicate limits to systems and ML collaborators.

Responsibilities

• Design controlled microbenchmarks and workload-level experiments that isolate compute throughput, memory-hierarchy behavior, data movement, and contention on external GPU and ASIC targets.
• Build repeatable characterization protocols that record workload, hardware, software, configuration, and measurement conditions so comparisons across targets are traceable.
• Develop and validate performance models against measured behavior; quantify prediction error, uncertainty, and the conditions under which a model transfers or ceases to transfer.
• Use profiler evidence and end-to-end measurements to distinguish compute, memory, communication, and interference limits rather than treating peak specifications as attainable performance.
• Publish decision-ready capability profiles and methodological caveats for compute-world-model, compiler, and runtime partners, including the evidence behind each conclusion.
• Partner with GPU Systems & Fabric on multi-device measurements and incorporate relevant data-movement characteristics into profiles, while leaving collective and fabric optimization to that team.

Skills

Accelerator architecture

Performance modeling

Benchmark design

Profiling methods

Data movement

Job description

General Diffusion, Inc. in San Francisco seeks a Member of Technical Staff to develop portable measurements and predictive performance models for external GPUs and ASICs, covering compute, memory, data movement, and contention.

You will produce traceable, evidence-backed capability profiles for compute-world-model, compiler, and runtime partners. The role emphasizes calibrating models to measurements, designing repeatable experiments, and collaborating with GPU Systems & Fabric on multi-device