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Director Nvidia Research Jobs (NOW HIRING)

You will help researchers adopt NVIDIA's AI and accelerated computing platforms to push the ... direct work on frontier AI systems. Ways to stand out from the crowd: * Experience with NVIDIA AI ...

NVIDIA is seeking a Director of Neural Graphics Software and Chips to join our team in Santa Clara ... research breakthroughs into hardware features, shipping platform capabilities, and API/shader ...

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... Identify, research, consult and prepare technical memoranda for complex transactions. Bring a point ...

Channel Sales Manager, NVIDIA Focus

Sacramento, CA · On-site

$162K/yr

... Directors (PMDs), focus on building relationships with vendor sales and alliance teams to uncover ... development, research, materials consolidation, stakeholder coordination, note capture, and ...

AI Security Engineer

Santa Clara, CA · On-site +1

$90 - $130/hr

As a Machine Learning Engineer, you'll work alongside NVIDIA's research and engineering teams ... This role is directed at assessing, and improving the safety and inclusivity of our LLM models in a ...

AI Security Engineer

Santa Clara, CA · On-site +1

$90 - $130/hr

As a Machine Learning Engineer, you'll work alongside NVIDIA's research and engineering teams ... This role is directed at assessing, and improving the safety and inclusivity of our LLM models in a ...

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Director Nvidia Research information

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$15.5K

$120K

$156.5K

How much do director nvidia research jobs pay per year?

As of Jun 9, 2026, the average yearly pay for director nvidia research in the United States is $119,966.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,000.00 and $141,000.00 per year, depending on experience, location, and employer.

What is the difference between Director Nvidia Research vs Research Scientist Nvidia?

AspectDirector Nvidia ResearchResearch Scientist Nvidia
Required CredentialsAdvanced degrees (Ph.D.), extensive research experience, leadership skillsMaster's or Ph.D., strong research background
Work EnvironmentLeads research teams, strategic planning, cross-department collaborationConducts independent or team research, experimental work
Employer & Industry UsageUsed in R&D divisions of Nvidia and similar tech companiesCommon in academic and corporate research labs, including Nvidia
Search & Comparison IntentUnderstanding leadership roles in Nvidia researchExploring research roles at Nvidia

The main difference between a Director Nvidia Research and a Research Scientist Nvidia lies in their responsibilities and seniority. The Director oversees research strategy and manages teams, while the Research Scientist focuses on conducting research projects. Both roles require strong technical credentials, but the director position emphasizes leadership and strategic planning.

More about Director Nvidia Research jobs
What cities are hiring for Director Nvidia Research jobs? Cities with the most Director Nvidia Research job openings:
What are the most commonly searched types of Nvidia Research jobs? The most popular types of Nvidia Research jobs are:
What states have the most Director Nvidia Research jobs? States with the most job openings for Director Nvidia Research jobs include:
Infographic showing various Director Nvidia Research job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 86% Full Time, 11% Part Time, 1% Temporary, and 1% Contract. Highlights an 84% Physical, 8% Hybrid, and 8% Remote job distribution, with an average salary of $119,966 per year, or $57.7 per hour.
Manager, Deep Learning - Autonomous Vehicles and Robotics

Manager, Deep Learning - Autonomous Vehicles and Robotics

Nvidia

Santa Clara, CA

Full-time

Posted 17 days ago


Job description

Join our Deep Learning Engineering team within NVIDIA's Tegra Solutions Engineering organization, where we deliver production-quality deep learning solutions for autonomous vehicles and robotics on edge hardware. As a key member of our team, you'll lead a group of highly skilled engineers. We work at the intersection of modern model architectures, compiler technology, and embedded deployment. Application areas include end-to-end autonomous driving, vision-language-action models, multi-camera perception, and robotic foundation models. You'll define and drive strategic technical initiatives, working directly with automotive OEMs and robotics partners to solve their toughest optimization challenges on NVIDIA DRIVE and Jetson platforms. You'll coordinate extensively with NVIDIA Research, hardware, and compiler teams to advance the state-of-the-art in deep learning for physical AI!

What you'll be doing:

  • Lead and develop a team of deep learning engineers delivering inference optimization and model enablement solutions for automotive and robotics customers.

  • Drive end-to-end technical engagements with OEM partners, owning scoping, resource allocation, and delivery of production-quality solutions.

  • Set technical direction on how modern architectures (transformers, vision-language models, state space models) are optimized and deployed on GPU and SOC platforms.

  • Partner with compiler, runtime, and hardware teams to connect customer workload patterns with platform capabilities and roadmap priorities.

  • Collaborate with NVIDIA Research and internal deep learning teams to bring brand new techniques into production!

  • Represent NVIDIA externally at partner reviews, conferences, and industry forums.

What we need to see:

  • Master's degree or equivalent experience in Computer Science, Electrical Engineering, or a related field.

  • 8+ years of overall experience with at least 5 years in deep learning model optimization, inference engineering, or neural network compilation.

  • 4+ years of team leadership experience

  • Proven ability to manage concurrent technical customer engagements and deliver under production constraints.

  • Strong knowledge of current DL architectures and inference optimization toolchains (TensorRT or equivalent).

  • Excellent communication skills with the ability to engage credibly with both OEM engineering leadership and deep technical ICs.

Ways to stand out from the crowd:

  • Experience leading DL optimization teams in the autonomous vehicle or robotics domain with direct OEM or Tier-1 engagement.

  • Background in training pipeline optimization, curriculum design, or end-to-end autonomous driving architectures.

  • Experience with ML compiler frameworks (TVM, MLIR, XLA, Triton) or inference runtime development.

  • Familiarity with automotive safety standards (ISO 26262, SOTIF) and their implications for inference system design.

  • Track record of building engineering teams in growing competitive talent markets and experience with Agentic AI frameworks, tools, and protocols like LangChain, LangGraph, MCP or equivalent experience

The Deep Learning Engineering team within Tegra Solutions Engineering sits at the intersection of NVIDIA's most advanced AI technology and the customers. We work end-to-end: from architecture decisions with OEM engineering leadership, through optimization and deployment on DRIVE and Jetson platforms, to production vehicles and robots operating in the field. Our engineers engage directly with the world's leading automotive and robotics companies, solving problems that span next-generation network architectures, training infrastructure, inference optimization, and closed-loop simulation. We collaborate closely with NVIDIA Research, various NVIDIA AI teams, and hardware teams. The team is growing, and we are investing in building out our presence across multiple sites. If you want your work to ship on real autonomous systems and shape the platforms they run on, this is the team to join.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 3, and 272,000 USD - 431,250 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 26, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993