Member of Technical Staff, Kernel Engineering

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified

Salary

$200K-$400K From the posting source checked Jun 20, 2026

401(k) match

Reported not verified - source not recorded; source URL not recorded; timestamp not recorded

Was this benefit information wrong? Tell us.

Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

157% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Staff Plus From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Equity

Offered From the posting source checked Jun 20, 2026

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Member of Technical Staff, Kernel Engineering San Francisco, California, United States Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware-a position that took years to build. About the Role We're looking for a performance engineer to squeeze every FLOP out of modern accelerators. You'll write the kernels and low-level optimizations that make vLLM the fastest inference engine in the world. Your code will run on hundreds of accelerator types, from NVIDIA GPUs to emerging silicon. When hardware vendors develop new chips, they integrate with vLLM. You'll work directly with these teams to ensure we're extracting maximum performance from every generation of hardware. Skills and Qualifications Minimum qualifications: - Bachelor's degree or equivalent experience in computer science, engineering, or similar. - Deep experience writing CUDA kernels or equivalent (CuTeDSL, Triton, TileLang, Pallas). - Strong understanding of GPU architecture: memory hierarchy, warp scheduling, tiling, tensor cores. - Proficiency in C++ and Python with demonstrated ability to write high-performance code. - Experience with profiling tools (Nsight, rocprof) and performance optimization methodologies. - Obsession with benchmarks and squeezing every percentage point of speedup. Preferred qualifications: - Experience with ML-specific kernel optimization (FlashAttention, fused kernels). - Knowledge of quantization techniques (INT8, FP8, mixed-precision). - Familiarity with multiple accelerator platforms (NVIDIA, AMD, TPU, Intel). - Experience with compiler technologies (LLVM, MLIR, XLA). Bonus points if

Read the full description at jobs.ashbyhq.com. FewerJobs shows a preview and links to the original posting.