Senior Staff Engineer - AI Workloads & Storage
USD 189K-301K Senior-level Full Time
Tasks
- Align work with standards and open ecosystem
- Build and evaluate system and transactional architecture models
- Establish benchmarking methodology and best practices
- Identify optimal data placement for SSDs
- Lead performance analysis across inference runtime and Linux storage networking stack
- Mentor engineers and set technical direction
- Own AI workload characterization
- Partner cross functionally to deploy architectures
- Profile LLM inference RAG and training workloads
- Reduce write amplification and improve endurance
- Tune for latency throughput cost and GPU utilization
Perks/Benefits
- N/A
Skills/Tech-stack
Blktrace | C++ | EBPF | Endurance | FDP | FIO | Flash Translation Layer | Ftrace | GPUDirect Storage | Garbage Collection | Go | KV cache | LLM | Linux | MLCommons | MLPerf | NVMe | NVMe-oF | Perf | Python | RAG | RDMA | Rust | SNIA | SPDK | Storage.AI | Streams | TensorRT-LLM | Transformer | Translation Layer | Triton | UNVMe | VLLM | Wear leveling | Write amplification | ZNS
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI Systems Engineer | Engineer | Senior Staff Engineer | Staff Engineer | Systems Engineer
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