NVIDIA

Senior Solutions Architect, Generative AI Research

Remote, United States remote Entry $184,000 - $287,500
remote Technology & IT Salary listed Curated
Sign in to apply Free account — we bring you straight back to this role.

About the role

Join NVIDIA to help university researchers advance the next generation of foundation models, multimodal AI, reasoning systems, and AI agents! At NVIDIA, we build accelerated computing platforms for frontier AI research. We partner with faculty, graduate researchers, and campus research-computing teams that push model performance, efficiency, scale, and scientific impact. We are looking for a Senior Solutions Architect for our Higher Education and Research Team. This role supports academic developers working on LLMs, VLMs, pretraining, post-training, evaluation, inference studies, scalable systems, and agent behaviors such as tool use, planning, memory, and multi-agent coordination.
What you'll be doing:
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%.

What we need to see:
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.

Ways to stand out from the crowd:
Advance AI scholarship through publications, open-source contributions, benchmark leadership, technical workshops, tutorials, or academic lab collaborations.

Contribute to pretraining, post-training, RLHF/RLAIF, DPO, synthetic data, data curation, scaling laws, model efficiency, agent evaluation, or benchmark design.

Familiarity with AI agent methods like LangGraph, LlamaIndex, LangChain, CrewAI, AutoGen, Semantic Kernel, Google ADK, OpenAI Agents SDK, DSPy, MCP, or A2A.

Experience with NVIDIA NeMo (Agent Toolkit, Guardrails, Megatron, Framework, NIM), Nemotron, OSS, Transformer Engine, TensorRT-LLM, Triton, RAPIDS.

We are excited to meet researchers and builders who raise the technical bar and help universities move faster from idea to discovery!
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ ​
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 28, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Originally posted on Himalayas

Interview prep

Walk in with sharper answers.

Use this as a quick practice sheet before you speak with the employer.

Role
Technology & IT Python Senior Solutions Architect Generative remote

Likely questions

  1. Tell us about work you have done that is close to the Senior Solutions Architect, Generative AI Research role.
  2. How would you approach your first 30 days at NVIDIA?
  3. Which of Python, Senior and Solutions have you used recently, and what did it help you achieve?
  4. Describe a time you solved a problem without waiting to be told exactly what to do.
  5. How do you stay organised and communicate clearly when working remotely?

Prepare before the call

  • A recent example that proves your experience with Python, Senior and Solutions.
  • One short story with a problem, your action, and the result.
  • Two examples that show the strengths listed on your CV.
  • A clear reason why this role and company interest you.
  • Your availability, preferred work style, and salary expectations.

Ask them

  • What would success look like in the first 90 days?
  • What are the main problems this hire should help solve?
  • How does the team give feedback and measure good work?
  • What does a normal working week look like for this role?
Practice line

I am interested in the Senior Solutions Architect, Generative AI Research role because I can bring practical experience in Python, Senior and Solutions, learn the team quickly, and contribute to the outcomes NVIDIA needs from this hire.

Related jobs.

More roles from this company or category.