Samsung Semiconductor
Senior Staff Engineer - AI Workloads & Storage
San Jose, California, United States · Staff+
Sponsorship not specified$10k-$15kDetected 19 hours ago
PythonRustC++CAlgorithmsLinuxMachine LearningNLPLLMsRAGExcelRecruitingResearchLeadershipMentoring
Stay score
odds of building a lasting career here
42Risky
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level I)39
Fits your clock70
Thin sponsorship signal and lottery-bound (~15% per draw). A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
Level I$152,7971 entry
Level II$187,0752 entries
Level III$221,3743 entries
Level IV$255,6534 entries
The bottom of this range ($10,000) is below the Level I prevailing wage of $152,797. An H-1B cannot be filed below the prevailing wage, so an offer at the floor of this band could not be sponsored as posted.
DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · San Jose-Sunnyvale-Santa Clara, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
Employer immigration record
from this employer's Department of Labor filings
Green-card filing pattern in this occupation
Context, not a finding about this posting: of this employer's 12 green-card filings in this occupation, 100% were for a worker who already held the job.
Green-card intent detected
Samsung Semiconductor, Inc. obtained a prevailing wage determination for Electrical Engineers in San Jose, CALIFORNIA on 2026-06-09. No matching green-card filing appears in our data yet. The determination expires in 1 day (2026-09-06), and a green-card filing must follow before then or the employer starts over.+1 more active determination on file
Green-card follow-through: 44%
Of 16 labor certifications old enough to have been used, 9 expired without the employer filing the next step. Median time from filing to decision: 496 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.
Files H-1B transfers
126 transfer filings in the last year, covering 435 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
Community outcomes
No reports yet — be the first to help the next applicant.
About the role
- Please Note: To provide the best candidate experience amidst our high application volumes, each candidate is limited to 10 applications across all open jobs within a 6-month period.
- Advancing the World's Technology Together Our technology solutions power the tools you use every day--including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more.
- We believe innovation and growth are driven by an inclusive culture and a diverse workforce.
Responsibilities
- Own AI workload characterization. Profile production and emerging LLM inference, RAG, and training workloads to quantify their I/O, bandwidth, latency, and capacity demands, and turn those findings into concrete storage and memory-hierarchy design decisions.
- Lead deep-dive performance analysis spanning the inference runtime, the Linux storage and networking stack, and the underlying hardware, tuning for latency, throughput, cost, and GPU utilization.
- Build and evaluate transactional and system-level models of proposed architectures to de-risk decisions before hardware exists, and validate them against measured behavior.
- Set technical direction others build on. Make build-vs-buy and architectural calls, establish benchmarking methodology and best practices, and mentor engineers across the org.
- Partner cross-functionally with product, hardware, and research teams, and with external vendors and partners, to bring architectures from concept to deployment.
- Own AI workload characterization.
- Profile production and emerging LLM inference, RAG, and training workloads to quantify their I/O, bandwidth, latency, and capacity demands, and turn those findings into concrete storage and memory-hierarchy design decisions.
- you will characterize real AI workloads, translate what you learn into architecture, and drive that direction across inference, platform, and hardware teams.
Requirements
- Bachelor's degree 15+ years relevant industry experience or Master's degree 13+ years' experience or PhD with 10+ years relevant industry experience.
- Extensive experience (typically 10-15+ years ) in systems, storage, or ML-systems software, with a track record of architecting systems that materially improved performance, reliability, or cost.
- 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.
- Experience with user-mode storage access frameworks: SPDK, uNVMe, libvfn, or similar.
- 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
- Demonstrated technical leadership and cross-team influence: setting direction, driving decisions across organizational boundaries, and mentoring senior engineers.
- Deep systems-level understanding of the Linux storage stack (block layer, I/O scheduling, NVMe) and of NAND/SSD internals (flash-translation layer, garbage collection, endurance/write-amplification, latency behavior), plus hands-on performance analysis skill (e.g., perf, ftrace, eBPF, blktrace, fio).
- Preferred Qualification
- Understanding of GPU and TPU architecture (memory hierarchy, interconnects, and how accelerator design shapes I/O and data-movement demands) is highly desired.
- SSD firmware experience - flash-translation layer, wear-leveling and garbage-collection algorithms, and data-placement features such as FDP / streams / ZNS - ideally paired with the ability to co-design firmware and host-side placement policy from workload characterization.
Nice to have
- Working knowledge of modern AI inference, especially transformer architectures - attention, KV cache, batching, and the memory/compute trade-offs of serving large models.
- Fluency in Python plus a systems language (C/C++, Rust, or Go).
- MS or PhD in Computer Science, Electrical/Computer Engineering, or a related field preferred - or equivalent practical experience.
Skills
- Advancing the World's Technology Together
Compensation
- $189,000 - $301,000 USD
Benefits
- This is in addition to our diverse package of benefits centered around the wellbeing of our employees and their loved ones.
- In addition to the usual Medical/Dental/Vision/401k, our inclusive rewards plan empowers our people to care for their whole selves.
- Enjoy Time Away You'll start with 4+ weeks of paid time off a year, plus holidays and sick leave, to rest and recharge.
- Care for Family Whatever family means to you, we want to support you along the way-including a stipend for fertility care or adoption, medical travel support, and virtual vet care for your fur babies.
- Prioritize Emotional Wellness With on-demand apps and free confidential therapy sessions, you'll have support no matter where you are.
- Embrace Flexibility Benefits are best when you have the space to use them.
- That's why we facilitate a flexible environment so you can find the right balance for you.
- NVMe (including ZNS, Flexible Data Placement / FDP), open-channel SSDs, computational storage - and with PCIe Gen5, CXL, and large-scale GPU-cluster storage (VAST, WEKA, Lustre, Ceph).
- Our onsite Café and gym, plus virtual classes, make it easier.
Company info
- We are looking for a Sr Staff Engineer who lives at the intersection of AI inference systems and storage/systems software.
- Our Commitment to Innovation and Fairness At Samsung Semiconductor, we use Artificial Intelligence (AI) tools in the recruitment process to enhance efficiency.
- Applicant AI Use Policy At Samsung Semiconductor, we su
- Collaborate with key customers to identify differentiating SSD capabilities for AI workloads, and develop proof-of-concept implementations as part of those customer engagements - turning workload insights into demonstrable data-path, tiering, and data-placement wins.
Equal opportunity
- Employment Policy
- Samsung Semiconductor takes pride in being an equal opportunity workplace dedicated to fostering an environment where all individuals feel valued and empowered to excel, regardless of race, religion, color, age, disability, sex, gender identity, sexual orientation, ancestry, genetic information, marital status, national origin, political affiliation, or veteran status.
- When selecting team members, we prioritize talent and qualities such as humility, kindness, and dedication.
- We extend comprehensive accommodations throughout our recruiting processes for candidates with disabilities, long-term conditions, neurodivergent individuals, or those requiring pregnancy-related support.
Apply directly at Samsung Semiconductor →Create a free account for alerts like thisView Samsung Semiconductor immigration profile
This listing is sourced directly from Samsung Semiconductor's careers page and normalized into a canonical job model.