13 days ago
Base Salary
$224k - $357k/yr
Responsibilities
- Advise partner engineering teams on architecture, code, and integration for Omniverse and AI-enabled solutions.
- Build technical expertise through prototyping, technical integrations, and reference architectures involving NVIDIA Cosmos, Omniverse, APIs, USD, NIMs, and Blueprints.
- Create sample code, guides, demonstration pipelines, and other technical enablement resources.
- Engage software organizations and technical decision-makers to solve integration challenges and promote best practices.
- Represent partner needs and field-deployment feedback to NVIDIA product and engineering teams to influence product roadmaps.
- Support product launches and technical go-to-market activities through technical validation, solution demonstrations, and partner-facing materials.
- Guide partners and startups through onboarding and integration with NVIDIA programs and foster co-innovation.
Requirements
- Master’s or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience.
- 12+ years of hands-on experience in a technical AI role, with strong emphasis on autonomous vehicle end-to-end models and GenAI model development.
- Production programming experience in Python or C++ and proficiency with Linux.
- Hands-on experience with GitLab, Docker, Kubernetes, and other DevOps tools.
- Strong understanding of autonomous vehicle systems, including sensors, dynamics, perception, prediction, planning, and control.
- Experience with deep learning and reinforcement learning algorithms and frameworks such as PyTorch.
- Experience collaborating across engineering, product, sales, and marketing teams and communicating complex technical concepts to diverse audiences.
- Experience leading technical collaborations involving architecture, code reviews, technical mentorship, and technical talks or workshops.
- Preferred experience with autonomous vehicle sensors, data curation pipelines, world models, simulation workflows, and tools.
- Preferred experience with agentic AI frameworks, tools, and protocols such as LangChain, LangGraph, and MCP.
- Understanding of multimodal LLMs, VLMs, and DiT computational characteristics.
- Experience deploying LLM models at scale on AWS, Azure, or GCP and optimizing inference latency, throughput, memory, and I/O utilization.
- Successful history of building developer communities and delivering technical enablement programs.
Benefits
- Competitive salary, equity, and a generous benefits package.
- The expected base salary range is USD 224,000–356,500, determined by location, experience, and other objective job-related factors.
- Applications will be accepted at least until November 3, 2026; the posting is for an existing vacancy.
Categories
Solutions Engineering
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.