Research Engineer/Scientist - Storage LLM
Listed on 2026-02-28
-
Software Development
Software Engineer, Machine Learning/ ML Engineer, Backend Developer, Cloud Engineer - Software
Research Engineer / Scientist - Storage for LLM
Location:
San Jose
Team:
Infrastructure
Employment Type:
Regular
Job Code: A244964
Responsibilities- Design and implement a distributed KV cache system to store and retrieve intermediate states (e.g., attention keys/values) for transformer-based LLMs across GPUs or nodes.
- Optimize low-latency access and eviction policies for caching long-context LLM inputs, token streams, and reused embeddings.
- Collaborate with inference and serving teams to integrate the cache with token streaming pipelines, batched decoding, and model parallelism.
- Develop cache consistency and synchronization protocols for multi-tenant, multi-request environments.
- Implement memory-aware sharding, eviction (e.g., windowed LRU,TTL), and replication strategies across GPUs or distributed memory backends.
- Monitor system performance and iterate on caching algorithms to reduce compute costs and response time for inference workloads.
- Evaluate and, where needed, extend open-source KV stores or build custom GPU-aware caching layers (e.g., CUDA, Triton, shared memory, RDMA).
Minimum Qualifications
- PhD in Computer Science, Applied Mathematics, Electrical Engineering, or a related technical field.
- Strong understanding of transformer-based model internals and how KV caching affects autoregressive decoding.
- Experience with distributed systems, memory management, and low-latency serving (RPC, gRPC, CUDA-aware networking).
- Familiarity with high-performance compute environments (NVIDIA GPUs, Tensor
RT, Triton Inference Server). - Proficiency in languages like C++, Rust, Go, or CUDA for systems-level development.
- Prior experience building inference-serving systems for LLMs (e.g., vLLM, SGLang, Faster Transformer, Deep Speed, Hugging Face Text Generation Inference).
- Experience with memory hierarchy optimization (HBM, NUMA, NVLink) and GPU-to-GPU communication (NCCL, GDR, GDS, Infini Band).
- Exposure to cache-aware scheduling, batching, and prefetching strategies in model serving.
The base salary range for this position in the selected city is $136,800 - $359,720 annually.
Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.
BenefitsBenefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).
EEC& Fair Chance Ordinance
For Los Angeles County (unincorporated) Candidates:
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