Senior Solutions Architect, Autonomous Driving - GenAI

Details

NVIDIA is building the world’s leading AI company, and we are looking for an expert AV and GenAI Solutions Architect to help customers adopt NVIDIA's full-stack technologies and to build and deploy solutions around Generative AI, Physical AI, and other GPU-accelerated technologies where intelligent agents can learn, reason, and interact with the world. As part of the Automotive Solutions Architecture team, you will work with accelerated computing platforms focused on development and test of autonomous vehicles, in-vehicle AI assistance, ride-sharing algorithms, and related workflows. You will be the first line of technical expertise between NVIDIA and customers, engaging directly with developers, researchers, and scientists at strategic customers and collaborating with business and engineering teams on product strategy.

Responsibilities

• Engage with customers to scope and develop solutions for building AV perception and planning models and pipelines, simulations, synthetic data generation, and software-in-the-loop testing.
• Design and advise on AI-enhanced manipulation and navigation workflows using NVIDIA Physical AI platforms and CUDA-X libraries.
• Provide hands-on technical mentorship to partners and customers on the NVIDIA GenAI stack and guide development and deployment of agentic AI workflows.
• Partner with Sales, Engineering, Product, and other Solution Architect teams to drive NVIDIA full-stack adoption and lead proof-of-concept evaluations.
• Build technical collateral (notebooks, GitHub repos, demos) applied to workflows such as AV and GenAI data curation, model training and validation, LLMs, VFMs, video encoding/decoding, and more.

Requirements

• Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience.
• 8+ years of hands-on experience in a technical AI role, with strong emphasis on end-to-end AV models and GenAI model development.
• Production coding experience in Python or C++ and proficiency with Linux.
• Hands-on experience with DevOps tools such as GitLab, Docker, and Kubernetes.
• Strong understanding of AV systems (sensors, dynamics, perception, prediction, planning, control).
• Experience with deep learning (DL) and reinforcement learning (RL) algorithms and frameworks such as PyTorch.
• Effective verbal and written communication and technical presentation skills; ability to work cross-functionally with engineering/research, product, sales, and marketing teams.
• Self-starter with a vision for growth and a passion for continuous learning and sharing findings.

Ways to stand out

• Experience with AV sensors, data curation pipelines, world models, simulation workflows and tools such as CARLA.
• Experience with agentic AI frameworks and tools (LangChain, LangGraph, MCP or equivalent).
• Understanding computational characteristics of multimodal models (LLMs, VLMs, DiT, VFMs) and model deployment considerations.
• Experience deploying LLMs at scale on cloud providers (AWS, Azure, GCP).
• Proven track record profiling and optimizing inference latency/throughput and memory/I/O utilization.

Compensation & Benefits

• Base salary ranges (location- and level-dependent):
  • Level 4: 184,000 USD - 287,500 USD per year
  • Level 5: 224,000 USD - 356,500 USD per year
• Eligible for equity and company benefits. More benefits information: https://www.nvidia.com/en-us/benefits/

Applications for this job will be accepted at least until July 29, 2025.

NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment.