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Full Time Nvidia Robotics Jobs (NOW HIRING)

MOBY Robotics

Autonomy & Software Engineer

Miami, FL · On-site

... (full-time, internship, or substantial research/project work) * Solid understanding of core ... Experience with underwater robotics (AUVs, ROVs) or marine/subsea systems Experience with NVIDIA ...

Carbon Robotics

Technical Recruiter

Seattle, WA · On-site

$120K - $135K/yr

The Carbon Robotics LaserWeederâ„¢ leverages advanced robotics, computer vision, AI/deep learning ... With $157 million in funding from prominent investors such as BOND, NVentures (NVIDIA's venture arm ...

Carbon Robotics

Technical Recruiter

Seattle, WA · On-site +1

$120K - $135K/yr

The Carbon Robotics LaserWeederâ„¢ leverages advanced robotics, computer vision, AI/deep learning ... With $157 million in funding from prominent investors such as BOND, NVentures (NVIDIA's venture arm ...

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Full Time Nvidia Robotics information

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$84K

$96K

$116.5K

How much do full time nvidia robotics jobs pay per year?

As of Jun 27, 2026, the average yearly pay for full time nvidia robotics in the United States is $96,000.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $102,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals in a full-time Nvidia Robotics role, and how can they be addressed?

Professionals in a full-time Nvidia Robotics role often encounter challenges such as integrating cutting-edge AI algorithms with complex hardware, ensuring real-time performance, and collaborating across multidisciplinary teams. These challenges can be addressed by staying current with Nvidia's software frameworks, engaging in regular cross-team knowledge sharing, and actively participating in code reviews. Additionally, leveraging Nvidia's extensive documentation and internal resources helps to streamline troubleshooting and foster innovative problem-solving within the team.

What is the difference between Full Time Nvidia Robotics vs Full Time Nvidia AI Engineer?

AspectFull Time Nvidia RoboticsFull Time Nvidia AI Engineer
Required CredentialsBachelor's or higher in Robotics, Computer Science, or related fields; experience with robotics hardware and softwareBachelor's or higher in Computer Science, AI, or related fields; strong programming and machine learning skills
Work EnvironmentHands-on robotics labs, hardware integration, real-world testingSoftware development, algorithm design, data modeling
Employer & Industry UsageTech companies, research labs focusing on robotics applicationsTech firms, AI research centers, software companies

Full Time Nvidia Robotics roles focus on developing and testing robotic systems, requiring hardware and software skills. In contrast, Full Time Nvidia AI Engineer positions emphasize AI algorithm development and software engineering. Both roles demand strong technical credentials but differ in their primary focus and work environment.

What are the key skills and qualifications needed to thrive as a Full Time Nvidia Robotics Engineer, and why are they important?

To thrive as a Full Time Nvidia Robotics Engineer, you need a solid background in robotics, computer science, and machine learning, typically with a relevant degree such as in engineering or computer science. Familiarity with technical tools like ROS (Robot Operating System), CUDA, Python/C++, and deep learning frameworks, as well as experience with Nvidia hardware and SDKs, is essential. Strong problem-solving abilities, teamwork, and effective communication are vital soft skills to excel in collaborative, cross-disciplinary projects. These skills and qualifications are crucial for developing innovative robotics solutions that leverage Nvidia's advanced technologies in a rapidly evolving field.

What are Full Time Nvidia Robotics jobs?

Full Time Nvidia Robotics jobs refer to professional positions at Nvidia that focus on developing, testing, and implementing robotics technologies. These roles may involve working on AI software, simulation platforms like Isaac Sim, robotics hardware integration, perception systems, and more. Employees in these positions typically collaborate with cross-functional teams to advance autonomous machines and robotics solutions using Nvidia's cutting-edge hardware and software. Candidates are often expected to have strong backgrounds in robotics, computer vision, machine learning, or related fields.
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What cities are hiring for Full Time Nvidia Robotics jobs? Cities with the most Full Time Nvidia Robotics job openings:
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Full Time Nvidia Robotics jobs near you
Infographic showing various Full Time Nvidia Robotics job openings in the United States as of June 2026, with employment types broken down into 100% Contract. Highlights an 88% Physical, 6% Hybrid, and 6% Remote job distribution, with an average salary of $96,000 per year, or $46.2 per hour.
Senior Research Engineer - Autonomous Vehicles

Senior Research Engineer - Autonomous Vehicles

Nvidia

Santa Clara, CA • On-site

$122K - $168K/yr

Full-time

Posted 22 days ago

Job description

We are recruiting top research engineers in the Autonomous Vehicles Research team at NVIDIA with strong expertise in software engineering and in artificial intelligence topics, such as deep learning, reinforcement learning, and generative modeling. You must have strong programming skills, a solid track record of training deep learning models at scale, and a good mathematical foundation to analyze new AI algorithms. We focus on AI models for autonomous driving such as agent behavior models, end-to-end AV architectures, AI safety, closed-loop training approaches, and AV foundation models (VLMs, reasoning models, etc.). We will be publishing at top venues and working with the broader scientific community. Communicating with different teams and domain scientists in different areas is essential.

The position will aid fundamental research with the freedom and bandwidth to conduct ground-breaking publishable research. At the same time, you will also have the opportunity to impact products and collaborate with teams that focus on AI products based on CUDA, physically-based simulation, graphics, natural language processing, autonomous driving, HW optimization, robotics, healthcare, and many more. NVIDIA has an open and nurturing atmosphere for research that encourages collaboration.

What you will be doing:

  • Develop large-scale supervised learning and reinforcement learning training frameworks to support multi-modal foundation models for AVs capable of running on thousands of GPUs;

  • Optimize GPU and cluster utilization for efficient model training and fine-tuning on massive datasets;

  • Implement scalable data loaders and preprocessors tailored for multimodal datasets, including videos, text, and sensor data;

  • Build and optimize simulation infrastructure (based on GPU-accelerated simulators) to support the training of driving policies for AVs at scale;

  • Collaborate with researchers to integrate cutting-edge model architectures into scalable training pipelines.

  • Develop sim-to-real transfer pipelines and work closely with the AV product team to deploy to real-world cars;

  • Propose scalable solutions that combine LLMs with policy learning.

  • Apply reinforcement learning to finetune multimodal LLMs.

  • Develop robust monitoring and debugging tools to ensure the reliability and performance of training workflows on large GPU clusters.

What we need to see:

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

  • 10+ years of full-time industry experience in large-scale MLOps and AI infrastructure.

  • Proven experience designing and optimizing distributed training systems with frameworks like PyTorch, JAX, or TensorFlow.

  • Deep familiarity with reinforcement learning algorithms like PPO, SAC, or Q-learning, including experience tuning hyperparameters and reward functions.

  • Familiarity with common policy learning techniques like reward shaping, domain randomization, curriculum learning.

  • Deep understanding of GPU acceleration, CUDA programming, and cluster management tools like Kubernetes.

  • Strong programming skills in Python and a high-performance language such as C++ for efficient system development.

  • Strong experience with large-scale GPU clusters, HPC environments, and job scheduling/orchestration tools (e.g., SLURM, Kubernetes).

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous research scientist with a genuine passion for advancing the state of AI? If so, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until January 13, 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

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