Staff Engineer - AI Workload Benchmarking

Prodapt ASIC services (Formerly Innovative Logic); San Jose (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Prodapt ASIC Services (formerly Innovative Logic) is seeking a Staff Engineer to lead AI workload benchmarking in our San Jose, CA office. This 5-day onsite role concentrates on extracting actionable performance insights for memory, storage, and AI infrastructure development.

You will benchmark with MLPerf Storage and related stacks, analyze NVMe SSDs, and deliver reproducible reports for senior engineers. Proficiency in Python, C/C++, Linux perf tools, and ML frameworks is essential.

Qualifications

• Bachelor's or Master's degree in computer science, computer engineering, electrical engineering, or related field.
• Advanced degree preferred.
• Experience in systems performance engineering or AI infrastructure benchmarking.
• Familiarity with storage performance and AI workloads.

Responsibilities

• Align benchmarking insights to leadership in memory and storage to inform product roadmaps.
• Enable performance-driven AI infrastructure design, validation, and standards engagement.

Skills

Python

C/C++

Linux performance benchmarking

PyTorch

ML frameworks

Education

Bachelor's or Master's in CS/CE/EE

Tools

blktrace

perf

eBPF/bpftrace

ftrace

iostat

fio

Job description

Prodapt ASIC Services (formerly Innovative Logic) provides end-to-end SoC/ASIC, FPGA, and embedded software solutions. Our design services cover the complete lifecycle from RTL to GDSII, covering domains like 3nm node physical design, UVM verification, DFT, and silicon bring-up for 5G, AI, and IoT.

We are looking for Staff Engineer - AI Workload Benchmarking in San Jose, CA and it's a 5-day onsite position.

Job Description:

• 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.

Job Responsibilities:

• 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.