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Staff Engineer - AI Workload Benchmarking
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The Norland Group
San Jose, CA (In Person)
$145,600 Salary, Full-Time
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Job Description
Staff Engineer
- AI Workload Benchmarking The Norland Group
- 4.6 San Jose, CA Job Details Contract $65
- $75 an hour 12 hours ago Qualifications AI models GPU programming Data storage GPU architecture Engineering testing Automation Tooling System performance optimization AI platforms (beyond public GPTs) Technical report writing Computational framework Performance testing IT monitoring tools C Model training Linux Systems analysis Data visualization Benchmarking Machine learning libraries Data analytics tools Scalability and Performance Testing (system development) Machine learning frameworks System performance monitoring
Full Job Description Location:
San Jose, CA Pay Rate:
$65- 75
Contract Duration:
6 months contractResponsibilities:
Align benchmarking insights to leadership in memory (HBM, DRAM, CXL) and storage (SSD/NAND) to inform product roadmaps. Enable next-generation AI infrastructure solutions through performance-driven system design, validation, and standards engagement.Requirements:
Bachelor's/ Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field; advanced degree preferred. Professional experience in systems performance engineering, storage performance, or AI infrastructure benchmarking. Demonstrated expertise with NVMe SSDs and storage stack performance analysis (block layer, page cache, file systems, asynchronous I/O). Hands-on experience with AI/ML workloads — LLM training and inference frameworks (PyTorch, vLLM, TensorRT-LLM, or equivalent), embedding pipelines, or vector databases (FAISS, Milvus, DiskANN, HNSW
). Strong proficiency with Linux performance and tracing tools: blktrace, perf, eBPF/bpftrace, ftrace, BCC, iostat, fio. Working knowledge of GPU systems and accelerator I/O paths Experience designing and executing benchmarks against industry standards (MLPerf Storage, or equivalent). Proficiency in Python for benchmarking automation, data analysis, and visualization; comfort with C/C++ for systems-level work. Proven ability to deliver structured technical reports, characterization studies, and reproducible benchmark artifacts to a senior engineering audience. We encourage Minorities, Women, Protected Veterans and Disabled individuals to apply for all positions that they may be qualified for. We maintain a drug-free workplace and perform pre-employment substance abuse testing and background checks If you are interested in this position, please submit your resume in a Word Document with the month and year that you have worked at each previous position to- and copy: 579601-Staff Engineer
- AI Workload Benchmarking to the email Subject Line.