Senior Forward Deployed Engineer I (AI Inference)
Tasks
- Architect distributed multi tenant LLM inference systems
- Build internal tooling and reusable blueprints
- Contribute performance fixes to open source inference ecosystems
- Debug KV cache locality issues
- Deploy production LLM serving with Kubernetes
- Drive compute efficiency with parallelism and batching
- Guide quantization for inference efficiency
- Implement continuous batching
- Implement prefill decode disaggregation
- Implement tiered prefix caching
- Lead AI inference delivery
- Optimize KV cache aware routing
- Optimize latency and throughput for LLMs
- Profile GPU memory utilization
- Support high concurrency production workloads
- Translate latency SLAs into infrastructure solutions
Perks/Benefits
- Conference reimbursement
- Employee assistance program
- Flexible time off
- LinkedIn Learning access
- Local Employee Meetups
- Training reimbursement
Skills/Tech-stack
AI Inference | Continuous batching | Data parallelism | Distributed Systems | FP4 | FP8 | GRPC | Go | KV cache | Kubernetes | LLM serving | Llm-d | MOE | Mixture of Experts | Nvidia Dynamo | Paged Attention | Python | Quantization | Ray Serve | SGLang | Tensor Parallelism | TensorRT-LLM | VLLM
Education
N/A
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