2 days ago
Base Salary
$152k - $242k/yr
Responsibilities
- Serve as the lead technical advisor for partners delivering reasoning-model, multimodal, fine-tuning, and model-serving solutions.
- Guide partners on fine-tuning, distillation, quantization, compression, benchmarking, evaluation, and inference approaches.
- Define benchmark plans, synthetic-data workflows, evaluation processes, and repeatable validation recipes.
- Advise on cluster sizing, GPU and network selection, storage, memory tradeoffs, latency, throughput, and production-readiness testing.
- Guide inference architecture across prefill/decode tradeoffs, batching, routing, disaggregated inference, and serving efficiency.
- Develop reference architectures, playbooks, benchmark recipes, TCO calculators, and sizing models using NVIDIA AI and inference tooling.
- Support pre-sales and post-sales engagements by translating model and infrastructure topics for partner and customer teams.
Requirements
- MSc or PhD in Computer Science, Electrical Engineering, Software Engineering, Machine Learning Engineering, or a related field, or equivalent experience.
- 5+ years of relevant experience with LLMs, VLMs, and large-scale inference systems, including fine-tuning, benchmarking, evaluation, optimization, and production deployment.
- Strong understanding of foundation-model data preparation, fine-tuning, post-training, evaluation, and inference.
- Familiarity with reasoning models, reinforcement learning, and synthetic-data generation and evaluation workflows.
- Strong Python programming skills and hands-on experience with PyTorch, JAX, or TensorFlow.
- Familiarity with Nemotron, NeMo, Dynamo, TensorRT-LLM, Triton, vLLM, and similar inference and optimization stacks.
- Strong communication and presentation skills for advising technical teams and executives.
- Preferred experience deploying large-scale AI systems in production, building benchmark suites or sizing and TCO models, contributing to open source, and working with GPU cluster technologies such as NVLink, InfiniBand, MPI, and NCCL.
Benefits
- Equity eligibility and a comprehensive benefits package.
- Applications are accepted at least until November 3, 2026.
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.