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Full Time Nvidia Robotics Jobs in Seattle, WA (NOW HIRING)

Technical Recruiter

Seattle, WA · On-site

$120K - $135K/yr

Carbon Robotics is the leader in physical AI for agriculture, helping farmers become more ... We offer competitive compensation and benefits to our full time US based* employees, including:

Technical Recruiter

Seattle, WA · On-site +1

$120K - $135K/yr

Carbon Robotics is the leader in physical AI for agriculture, helping farmers become more ... We offer competitive compensation and benefits to our full time US based* employees, including:

Wiring Harness Engineer

Seattle, WA · On-site +1

$125K - $150K/yr

Carbon Robotics is the leader in physical AI for agriculture, helping farmers become more ... including NVIDIA's NVentures and BOND. YouTube | X | Instagram | LinkedIn | News As a Wiring ...

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Full Time Nvidia Robotics information

See Seattle, WA salary details

$95.6K

$109.3K

$132.6K

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

As of Aug 22, 2026, the average yearly pay for full time nvidia robotics in Seattle, WA is $109,250.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,400.00 and $116,100.00 per year, depending on experience, location, and employer.

What is a full time Nvidia Robotics job?

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.

What are the key skills and qualifications needed to thrive as a full time Nvidia Robotics engineer?

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 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 most commonly searched types of Nvidia Robotics jobs in Seattle, WA?

The most popular types of Nvidia Robotics jobs in Seattle, WA are:

What are popular job titles related to Full Time Nvidia Robotics jobs in Seattle, WA?

For Full Time Nvidia Robotics jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Full Time Nvidia Robotics jobs in Seattle, WA look for?

The top searched job categories for Full Time Nvidia Robotics jobs in Seattle, WA are:

Infographic showing various Full Time Nvidia Robotics job openings in Seattle, WA as of August 2026, with employment types broken down into 88% Full Time, 7% Part Time, 4% Contract, and 1% Nights. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $109,250 per year, or $52.5 per hour.

Research Scientist, Robotics Research - PhD New College Grad 2026

NVIDIA

Seattle, WA

Full-time

Re-posted 8 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 246 rated software companies


Job description

US, WA, Seattle

Full time

JR2011473

NVIDIA is at the forefront of the AI and robotics revolution, and our robotics teams are on a mission to build the essential technology that can enable any company to become a robotics company. The Seattle Robotics Lab (https://research.nvidia.com/labs/srl/) is passionate about fundamental and applied robotics research across the full robotics stack, including perception, planning, control, reinforcement learning, imitation learning, and simulation. This research strives to transform research paradigms, transfer into NVIDIA's robotics and simulation products, and build new robotics markets for the world.

The Seattle Robotics Lab has led many influential works that have been presented at top robotics, AI, and computer vision conferences; these works include BayesSim (https://www.roboticsproceedings.org/rss15/p29.pdf) , cuRobo (https://curobo.org/) , DeXtreme (https://dextreme.org/) , DiSECT (https://diff-cutting-sim.github.io/) , Factory (https://research.nvidia.com/publication/2022-05_factory-fast-contact-robotic-assembly) , GraspNet (https://arxiv.org/pdf/1905.10520) , ITPS (https://yanweiw.github.io/itps/) , MimicGen (https://mimicgen.github.io/) , RVT (https://robotic-view-transformer.github.io/) , and SHAC (https://arxiv.org/abs/2204.07137) . (See our publications page (https://research.nvidia.com/labs/srl/publication/) for a complete list.) The work has deeply impacted the research community and NVIDIA products, including Isaac Sim (https://developer.nvidia.com/isaac/sim) , Isaac Lab (https://developer.nvidia.com/isaac/lab) , and Isaac Manipulator (https://developer.nvidia.com/isaac/manipulator) . Furthermore, SRL collaborates closely with other research and engineering teams to advance and use the Cosmos (https://www.nvidia.com/en-us/ai/cosmos/) and GR00T-N (https://developer.nvidia.com/isaac/gr00t) foundation models, as well as the Newton (https://developer.nvidia.com/blog/announcing-newton-an-open-source-physics-engine-for-robotics-simulation/) physics simulation engine. The team is targeting several grand challenges in robotics and is aiming to achieve never-before-seen capabilities within 2-3 years. We are looking for research scientists to play a pivotal role in these efforts. These scientists must have outstanding research and engineering skills, a proven research track record, strong supporting references, and a team-first approach.

What you will be doing:

  • Developing algorithms, models, and methods for robotic manipulation and loco-manipulation, for both industrial and household applications;
  • Integrating these methods into real-world robotic manipulation systems, including those consisting of collaborative robot arms, industrial robot arms, mobile manipulators, humanoids, and dexterous hands;
  • Contributing to multi-person research projects that require a diverse set of skills across the robotics and machine learning stack;
  • Engaging with the academic community through high-impact publications, conferences, workshops, and code releases;
  • Collaborating with product managers and engineering teams to transfer your research into NVIDIA products that will have real-world impact;
  • Mentoring interns joining NVIDIA during their PhD programs.

What we need to see:

  • Completing a PhD in Robotics, Machine Learning, Computer Science, Electrical Engineering, Mechanical Engineering, or a related field (or equivalent experience).
  • A strong research track record, with work published in top robotics and AI conferences and journals such as RSS, CoRL, ICRA, IROS, IJRR, T-RO, NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, and EMNLP.
  • Exceptional programming skills in Python, as well as proficiency in modern deep learning frameworks (PyTorch or JAX), robotics frameworks (ROS or ROS2), and physics simulation frameworks (Isaac Sim/Lab or MuJoCo). Familiarity with C++, CUDA, and Warp is a plus.
  • Exceptional communication, collaboration, and interpersonal skills, with significant experience working on teams.
  • Comfort in working through the complexities of simulation and real-world robotics, including debugging physics simulators and renderers under rapid development; selecting, setting up, maintaining, and enhancing complex robotics hardware; debugging real-world communication systems; and designing robust workflows for model training and evaluation.

The following research areas and applications are of particular interest:

  • Bimanual and dexterous manipulation
  • Mobile manipulation and humanoid loco-manipulation
  • Multisensory perception (e.g., vision, tactile, and force/torque sensing)
  • Simulation, sim-to-real, and real-to-sim
  • Vision-language-action (VLA) models, including architectural advancements, large-scale training, and test-time reasoning
  • Industrial applications, such as bin-picking, kitting, and assembly

The Seattle Robotics Lab is now located in a brand-new office in the vibrant Fremont neighborhood of Seattle.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD.

You will also be eligible for equity and benefits (https://www.nvidia.com/en-us/benefits/) .

Applications for this job will be accepted at least until July 28, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry.

Learn more about NVIDIA .


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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