Staff Engineer, AI Benchmarking & Inference Systems

S27a

San Francisco, New York (CA, NY)

Hybrid

USD 140,000 - 190,000

Full time

14 days+
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Benefits offered by this job

Generous PTO
Office stipend
Competitive healthcare (medical,Dental
Vision benefits
Conference support

Job summary

SemiAnalysis is seeking a highly motivated Member of Technical Staff to join our growing engineering team. You will contribute to inference benchmarks, system modeling, and the preparation of technical newsletters with potential authorship recognition.

We hire individuals at all experience levels and offer competitive compensation. As part of the process, you’ll complete a paid coding challenge reflecting daily tasks and collaborate with a global team across multiple AI and hardware domains.

Qualifications

  • Proactive, self-motivated, and capable of working independently in a global team.
  • Experience with ML frameworks such as PyTorch or JAX through professional experience, personal projects, or personal Substack blogs.
  • Solid understanding of at least 1 of the following: transformer architecture, LLM parallelism strategies, and/or CUDA parallel programming.

Responsibilities

  • Conduct training and inference benchmarks across AI accelerators (H100, Mi300X, TPUs, Trainium2) using PyTorch/JAX.
  • Author detailed reports analyzing benchmark results, hardware performance, scalability, and efficiency.
  • Develop system modelling using Python and NCCL for AI compute clusters from single-GPU to large scales.
  • Establish partnerships with cloud providers and AI hardware makers (AMD, NVIDIA, etc.).
  • Stay current on trends by attending NeurIPS, MLSys, GTC and related conferences.

Skills

PyTorch
JAX
Python
Transformer architecture
LLM parallelism

Tools

NCCL
CUDA
vLLM
SGLang

Job description

SemiAnalysis is seeking a highly motivated Member of Technical Staff to join our growing engineering team. You will contribute to inference benchmarks, system modeling, and the preparation of technical newsletters with potential authorship recognition.

We hire individuals at all experience levels and offer competitive compensation. As part of the process, you’ll complete a paid coding challenge reflecting daily tasks and collaborate with a global team across multiple AI and hardware domains.

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