1 day ago
Base Salary
$224k - $357k/yr
Responsibilities
- Advise partner engineering teams on architecture, code, integrations, and AI-enabled solutions involving Omniverse and related NVIDIA technologies.
- Build technical expertise through prototyping, technical integration, and creation of reference architectures for Cosmos and Omniverse.
- Create sample code, guides, demonstration pipelines, and enablement tools.
- Engage engineering teams, technical leaders, and 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, integrated-solution demonstrations, and partner-facing materials.
- Guide partners and startups through onboarding and integration with NVIDIA programs.
- Lead technical collaborations involving architecture, code reviews, technical mentorship, talks, and workshops.
Requirements
- Master’s degree or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience.
- 12+ years of hands-on experience in technical AI roles, with emphasis on autonomous vehicle end-to-end models and GenAI model development.
- Production programming experience in Python or C++, with proficiency in Linux.
- Hands-on experience with GitLab, Docker, and Kubernetes.
- 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 architectural design, code reviews, technical mentorship, and technical talks or workshops.
- Preferred: experience with AV sensors, data curation pipelines, world models, simulation workflows, and simulation tools.
- Preferred: experience with agentic AI frameworks, tools, and protocols such as LangChain, LangGraph, and MCP.
- Preferred: understanding of multimodal LLMs, VLMs, and DiT.
- Preferred: experience deploying LLMs at scale on AWS, Azure, or GCP and optimizing inference latency, throughput, memory, and I/O utilization.
- Preferred: experience building and scaling developer communities and technical enablement programs.
Benefits
- Competitive salaries and a generous benefits package.
- Eligible for equity and benefits.
- The base salary range is USD 224,000–356,500, determined by location, experience, and comparable employee pay.
- Applications will be accepted at least until September 27, 2026.
- This 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.