Senior Staff Engineer - AI Workloads & Storage

The role

This role involves characterizing AI workloads to drive storage and memory-hierarchy design decisions. You will lead technical direction across inference, platform, and hardware teams to build next-generation NAND/SSD storage systems.

What you will do

• Own AI workload characterization.
• Identify optimal data placement on flash.
• Collaborate with customers to develop proof-of-concept implementations.
• Lead deep-dive performance analysis of inference runtime and storage stacks.
• Build and evaluate transactional and system-level models of proposed architectures.
• Engage with standards and open ecosystems like SNIA and MLCommons.
• Set technical direction and establish benchmarking methodology.
• Partner cross-functionally with product, hardware, and research teams.

Required qualifications

• Bachelor's degree with 15+ years relevant industry experience or
• Master's degree with 13+ years' experience or
• PhD with 10+ years relevant industry experience.
• 10–15+ years in systems, storage, or ML-systems software.
• Demonstrated technical leadership and cross-team influence.
• Working knowledge of modern AI inference and transformer architectures.
• Deep systems-level understanding of the Linux storage stack and NAND/SSD internals.
• Hands-on performance analysis skill (e.g., perf, ftrace, eBPF, blktrace, fio).
• Fluency in Python plus a systems language (C/C++, Rust, or Go).

Nice to have

• MS or PhD in Computer Science, Electrical/Computer Engineering, or a related field
• Hands-on experience with the modern inference stack: vLLM, SGLang, LMCache, NVIDIA Dynamo, TensorRT-LLM, or Triton.
• Familiarity with GPU-adjacent data movement and memory frameworks: NIXL, DOCA / DOCA MemOps, GPUDirect Storage, RDMA, NVMe-oF, and BlueField / DPU offload.
• Understanding of GPU and TPU architecture.
• Experience with user-mode storage access frameworks: SPDK, uNVMe, libvfn, or similar.
• SSD firmware experience.
• AI-workload characterization and benchmarking experience, and familiarity with SNIA Storage.AI and MLCommons / MLPerf.
• Transactional / discrete-event or system-level modeling experience in frameworks such as SystemC, SimPy, or similar.
• Experience with SSD architecture and interfaces - NVMe (including ZNS, Flexible Data Placement / FDP), open-channel SSDs, computational storage - and with PCIe Gen5, CXL, and large-scale GPU-cluster s

Benefits

• Incentive opportunities based on individual and company performance.
• Medical/Dental/Vision
• 401k
• Charitable giving match
• 4+ weeks of paid time off a year, plus holidays and sick leave
• Stipend for fertility care or adoption
• Caregiver support
• Medical travel support
• On-demand apps and free confidential therapy sessions
• Onsite Café and gym
• Virtual classes
• Flexible environment

Before you apply

• Each candidate is limited to 10 applications across all open jobs within a 6-month period.
• AI tools should not be used to generate or assist with submitted content or live interview responses.
• By submitting an application, you agree not to disclose any confidential or proprietary information belonging to a current or former employer.

About the company

Samsung Semiconductor's Technology Enabling Development Lab (TED) focuses on host interface firmware layer at the intersection of system software and flash management firmware.