# Senior Solutions Architect, Generative AI Research

**Company**: NVIDIA
**Work arrangement**: remote
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-FL-Remote/Senior-Solutions-Architect--Generative-AI-Research_JR2019852?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_b1b5237d-614

## Description

Join NVIDIA to help university researchers advance the next generation of foundation models, multimodal AI, reasoning systems, and AI agents.

As a Senior Solutions Architect for our Higher Education and Research Team, you will support academic developers working on LLMs, VLMs, pretraining, post-training, evaluation, inference studies, scalable systems, and agent behaviors.

**Responsibilities:**

- Partner with universities to shape high-impact work on foundation models, generative AI, multimodal AI, reasoning systems, AI agents, and AI systems.

- Advise labs on GPU-accelerated training, inference studies, agent evaluation, tool-use methods, data pipelines, scaling experiments, and reproducible workflows.

- Help build research prototypes with researchers utilizing the NVIDIA full stack.

- Analyze throughput, memory, parallelism, latency, and scaling across workstations, multi-GPU servers, and campus HPC clusters.

- Translate lab feedback into technical examples, workshops, roadmap input, and adoption guidance for NVIDIA teams.

- Travel up to 20%.

**Requirements:**

- BS, MS or PhD in Computer Science, AI/ML, Electrical Engineering, Applied Mathematics, or a related technical field, or equivalent experience.

- 8+ years of hands-on experience with AI systems, accelerated computing, distributed training, inference studies, or research-scale generative AI workflows.

- Deep foundational AI expertise across LLMs, VLMs, multimodal models, reasoning, long-context models, fine-tuning, post-training, agentic AI, and evaluation.

- Strong systems fluency in PyTorch or JAX, Python, Linux, distributed AI, data loading, checkpointing, memory optimization, batching, scheduling, latency, and throughput.

- Experience guiding faculty, graduate researchers, and research-computing teams on benchmarks, reproducibility, reliability, safety, agent evaluation, and research impact.

- Clear communication, technical judgment, and comfort turning complex model, agent, and infrastructure questions into practical next steps for labs.

**Benefits:**

- Highly competitive salaries

- Comprehensive benefits package

- Equity eligibility

- Visit www.nvidiabenefits.com/ for more information

## Skills

### Required
- AI systems
- accelerated computing
- distributed training
- inference studies
- generative AI workflows
- LLMs
- VLMs
- multimodal models
- reasoning
- PyTorch
- JAX
- Python
- Linux
- distributed AI

### Nice to have
- publications
- open-source contributions
- benchmark leadership
- technical workshops
- academic lab collaborations
- pretraining
- post-training
- RLHF/RLAIF
- DPO
- synthetic data
- data curation
- scaling laws
- model efficiency
- agent evaluation
- benchmark design
- LangGraph
- LlamaIndex
- LangChain
- CrewAI
- AutoGen
- Semantic Kernel
- Google ADK
- OpenAI Agents SDK
- DSPy
- MCP
- A2A
- NVIDIA NeMo
- Nemotron
- OSS
- Transformer Engine
- TensorRT-LLM
- Triton
- RAPIDS

---

Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-FL-Remote/Senior-Solutions-Architect--Generative-AI-Research_JR2019852?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)