N

NVIDIA

Designs the chips and software that power AI

Technical Lead - GenAI, Autonomous Vehicles

Developer Relations & AdvocacyConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • A Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience is required.
  • At least 12 years of hands-on experience in a technical artificial intelligence role, with a strong emphasis on autonomous-vehicle end-to-end models and generative AI model development.
  • Experience writing production code in Python or C++, and proficiency with Linux.
  • Hands-on experience with DevOps tools such as 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.
  • Ability to collaborate across engineering, product, sales, and marketing teams, and to simplify complex technical concepts for diverse audiences.
  • Experience leading technical collaborations with engineering and product teams, including architectural design, code reviews, technical mentorship, and delivery of technical talks or workshops.
  • Ability to work independently and a commitment to continuous learning and sharing findings across the team.

Responsibilities

  • Serve as a technical advisor and problem solver with partner engineering teams, collaborating on architecture, code, and integration for Omniverse and artificial intelligence-enabled solutions.
  • Develop and maintain deep technical expertise in NVIDIA Cosmos and Omniverse platforms and related technologies, including APIs, USD, NIMs, and Blueprints, through prototyping, technical integration, and creation of reference architectures.
  • Advise on technical enablement resources such as sample code, guides, demonstration pipelines, and tools that highlight how technologies solve real-world problems.
  • Engage with partner software organizations, including engineering teams, technical leaders, and decision-makers, to understand goals, solve technical challenges, and promote best practices for successful integrations.
  • Represent partner technical needs and feedback to NVIDIA's internal product and engineering teams, supplying actionable insights from field deployments to influence product roadmaps.
  • Support product launches and technical go-to-market activities by providing technical validation, demonstrating integrated solutions, and ensuring the quality of customer- and partner-facing materials.
  • Guide partners and startups through onboarding and integration with NVIDIA's programs, fostering co-innovation and development of next-generation solutions.

Desired Qualifications

  • Experience with autonomous-vehicle sensors, data curation pipelines, world models, and simulation workflows and tools.
  • Experience with agentic artificial intelligence frameworks, tools, and protocols such as LangChain, LangGraph, and MCP, or equivalent experience.
  • Understanding of the computational characteristics of multimodal large language models, vision-language models, and diffusion transformers.
  • Experience deploying large language models at scale on mainstream cloud providers such as AWS, Azure, or GCP, with a proven track record of profiling and optimizing inference latency and throughput, memory utilization, and input/output utilization.
  • A successful history of building and scaling developer communities and delivering impactful technical enablement programs.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

Recently Posted Jobs

Explore more opportunities at NVIDIA

See more jobs