Sr LLMOps Engineer -— LLM Inference & Model Optimization
Gnani.ai (Gnani Innovations Private Limited) (company site, opens in a new tab)6–10 yrsBengaluruOn-siteDirect career pageEst. 30–55 LPA
Posted on 8 Sept
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Job description
Structured overview of role & requirements
About This Role
- Own and optimize large language model serving stack and infrastructure across vLLM, SGLang, and NVIDIA Dynamo for real-time voice AI under strict latency and cost constraints.
- Lead model optimization efforts including quantization, distillation, pruning, and speculative decoding to maintain accuracy while reducing inference cost.
- Profile and tune low-level CUDA/Triton kernels and maintain production-grade inference platform with scalable deployments, on-call responsibility, and continuous evaluation.
Minimum Requirements
- 6 to 10 years total experience, with 3+ years owning large-scale LLM or speech inference production systems.
- Proven experience owning end-to-end inference platform including architecture, SLOs, capacity, cost management, deployment safety, and on-call support.
- Proficient in writing or substantially tuning custom CUDA or Triton kernels deployed in production.
- Experience with MoE model serving at scale, expert parallelism, routing, and distributed multi-node system profiling and debugging.
Ideal Candidate Profile
- Strong expertise in deep profiling and performance optimization of GPU inference workloads in production, with demonstrated record fixing utilization issues.
- Familiarity with managing and implementing multi-layer inference optimizations, balancing latency, accuracy, and cost under real-time constraints.
- Experience contributing to or leading technical direction for open-source large model serving or kernel projects (e.g. vLLM, SGLang) or equivalent highly technical platforms.