... NVIDIA invests across the robotics stack. What we need to see: * BS, MS, or PhD in Robotics, Computer Science, Electrical/Mechanical Engineering, or a related field (or equivalent experience). * 12 ...
... NVIDIA invests across the robotics stack. What we need to see: * BS, MS, or PhD in Robotics, Computer Science, Electrical/Mechanical Engineering, or a related field (or equivalent experience). * 12 ...
... NVIDIA invests across the robotics stack. What we need to see: * BS, MS, or PhD in Robotics, Computer Science, Electrical/Mechanical Engineering, or a related field (or equivalent experience). * 12 ...
... NVIDIA invests across the robotics stack. What we need to see: * BS, MS, or PhD in Robotics, Computer Science, Electrical/Mechanical Engineering, or a related field (or equivalent experience). * 12 ...
... avionics, electrical, mechanical, and other engineering teams. Qualifications & Experience ... Experience with NVIDIA edge compute, CUDA/TensorRT, ROS 2, MAVLink, or comparable robotics and ...
Quick apply
... avionics, electrical, mechanical, and other engineering teams. Qualifications & Experience ... Experience with NVIDIA edge compute, CUDA/TensorRT, ROS 2, MAVLink, or comparable robotics and ...
... avionics, electrical, mechanical, and other engineering teams. Qualifications & Experience ... Experience with NVIDIA edge compute, CUDA/TensorRT, ROS 2, MAVLink, or comparable robotics and ...
... avionics, electrical, mechanical, and other engineering teams. Qualifications & Experience ... Experience with NVIDIA edge compute, CUDA/TensorRT, ROS 2, MAVLink, or comparable robotics and ...
... avionics, electrical, mechanical, and other engineering teams. Qualifications & Experience ... Experience with NVIDIA edge compute, CUDA/TensorRT, ROS 2, MAVLink, or comparable robotics and ...
... avionics, electrical, mechanical, and other engineering teams. Qualifications & Experience ... Experience with NVIDIA edge compute, CUDA/TensorRT, ROS 2, MAVLink, or comparable robotics and ...
Electrical Engineer
Fredericksburg, VA · On-site
Collaborate with mechanical engineers to ensure enclosure and cable routing compatibility. * AR ... Familiarity with AI/ML edge processing (e.g., ESP32, NVIDIA Jetson Nano, Google Coral)
Quick apply
Electrical Engineer
Fredericksburg, VA · On-site
Collaborate with mechanical engineers to ensure enclosure and cable routing compatibility. * AR ... Familiarity with AI/ML edge processing (e.g., ESP32, NVIDIA Jetson Nano, Google Coral)
Electrical Engineer
Fredericksburg, VA · On-site
Collaborate with mechanical engineers to ensure enclosure and cable routing compatibility. * AR ... Familiarity with AI/ML edge processing (e.g., ESP32, NVIDIA Jetson Nano, Google Coral)
Electrical Engineer
Fredericksburg, VA · On-site
Collaborate with mechanical engineers to ensure enclosure and cable routing compatibility. * AR ... Familiarity with AI/ML edge processing (e.g., ESP32, NVIDIA Jetson Nano, Google Coral)
Collaborate with mechanical engineers to ensure enclosure and cable routing compatibility. * AR ... Familiarity with AI/ML edge processing (e.g., ESP32, NVIDIA Jetson Nano, Google Coral)
Collaborate with mechanical engineers to ensure enclosure and cable routing compatibility. * AR ... Familiarity with AI/ML edge processing (e.g., ESP32, NVIDIA Jetson Nano, Google Coral)
Solutions Engineer - New Products
Herndon, VA · On-site
$99 - $132/hr
Bachelor's degree in a STEM discipline (e.g., Aerospace, Computer Science, Electrical or Mechanical ... Experience with embedded Linux / edge compute platforms (NVIDIA Jetson, Qualcomm‑based SoCs ...
Solutions Engineer - New Products
Herndon, VA · On-site
$99 - $132/hr
Bachelor's degree in a STEM discipline (e.g., Aerospace, Computer Science, Electrical or Mechanical ... Experience with embedded Linux / edge compute platforms (NVIDIA Jetson, Qualcomm‑based SoCs ...
Collaborate with mechanical engineers to ensure enclosure and cable routing compatibility. * AR ... Familiarity with AI/ML edge processing (e.g., ESP32, NVIDIA Jetson Nano, Google Coral)
New
Collaborate with mechanical engineers to ensure enclosure and cable routing compatibility. * AR ... Familiarity with AI/ML edge processing (e.g., ESP32, NVIDIA Jetson Nano, Google Coral)
New
AI Infrastructure Engineer - Emerging Technologies
Ashburn, VA · On-site
$109K - $144K/yr
Analyze current and future AI compute platforms including NVIDIA GPU architectures, ARM-based ... Assess implications of ultra-high-density AI deployments on mechanical system design, water usage ...
AI Infrastructure Engineer - Emerging Technologies
Ashburn, VA · On-site
$109K - $144K/yr
Analyze current and future AI compute platforms including NVIDIA GPU architectures, ARM-based ... Assess implications of ultra-high-density AI deployments on mechanical system design, water usage ...
... NVIDIA Jetson) often used in IoT and UGS-like applications. * Operating Systems: Embedded Linux ... Firmware Update Mechanisms: Over-the-Air (OTA) updates, bootloaders, secure firmware update ...
... NVIDIA Jetson) often used in IoT and UGS-like applications. * Operating Systems: Embedded Linux ... Firmware Update Mechanisms: Over-the-Air (OTA) updates, bootloaders, secure firmware update ...
Nvidia Mechanical Engineer information
See Virginia salary details
$45.1K - $56K
2% of jobs
$56K - $66.9K
6% of jobs
$66.9K - $77.8K
12% of jobs
$80.7K is the 25th percentile. Wages below this are outliers.
$77.8K - $88.7K
18% of jobs
The median wage is $95.8K / yr.
$88.7K - $99.6K
18% of jobs
$99.6K - $110.5K
13% of jobs
$118K is the 75th percentile. Wages above this are outliers.
$110.5K - $121.4K
9% of jobs
$121.4K - $132.4K
17% of jobs
$132.4K - $143.3K
2% of jobs
$143.3K - $154.2K
1% of jobs
$154.2K - $165.1K
2% of jobs
$45.1K
$102K
$165.1K
How much do nvidia mechanical engineer jobs pay per year?
What is an Nvidia mechanical engineer?
An Nvidia Mechanical Engineer designs, analyzes, and tests mechanical components for cutting-edge computing hardware, including GPUs, AI accelerators, and data center systems. They collaborate with cross-functional teams to ensure thermal performance, structural integrity, and manufacturability of products. Their work involves CAD modeling, simulations, prototyping, and validation to optimize product performance and reliability.
What does an Nvidia mechanical engineer do?
As an Nvidia Mechanical Engineer, your daily activities might involve designing and analyzing components for GPUs or other hardware, creating 3D models, running simulations, and validating prototypes. You’ll participate in regular cross-functional meetings with electrical engineering, thermal, and manufacturing teams to ensure seamless integration of design requirements. The environment is fast-paced and highly collaborative, fostering open communication and idea-sharing. This teamwork-focused atmosphere helps drive innovation and ensures products meet rigorous performance and quality standards.
What are the key skills and qualifications needed for an Nvidia mechanical engineer?
To thrive as an Nvidia Mechanical Engineer, you need a solid background in mechanical engineering principles, thermal management, and structural analysis, typically supported by a relevant engineering degree. Familiarity with CAD/CAE software (such as SolidWorks or ANSYS) and experience with product development cycles are highly valued, along with certifications like PE or EIT being advantageous. Strong problem-solving abilities, teamwork, and effective communication skills help engineers collaborate efficiently across multidisciplinary teams. These skills ensure innovative, reliable hardware solutions that support Nvidia's cutting-edge technology goals.
Can Nvidia Mechanical Engineers work at NVIDIA?
What are the most commonly searched types of Nvidia Mechanical Engineer jobs in Virginia?
The most popular types of Nvidia Mechanical Engineer jobs in Virginia are:
What are popular job titles related to Nvidia Mechanical Engineer jobs in Virginia?
For Nvidia Mechanical Engineer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Nvidia Mechanical Engineer jobs in Virginia look for?
The top searched job categories for Nvidia Mechanical Engineer jobs in Virginia are:

Senior Manager, Software Engineering - Robotics Manipulation
Charlottesville, VA • On-site
9.6
Based on 18 frontline employees who took The Breakroom Quiz
7th of 246 rated software companies
Great coworkers
People enjoy working here
Good employer
Respectful managers
Learn new skills
Full-time
Re-posted 16 days ago
Job description
NVIDIA is the engine of modern AI, and robotics is where AI meets the physical world. The Isaac robotics platform - spanning Isaac Sim, Isaac Lab, Isaac ROS, the foundation models behind Isaac GR00T, and the accelerated libraries that run on Jetson and in the data center - is how the world's developers and industrial leaders build intelligent robots.
We are looking for an exceptional engineering leader and manager to head up Isaac for Manipulation: giving robotic arms and dexterous systems the perception, grasping, motion, and learned skills they need to do real, impactful work. You will be responsible for the strategy, roadmap, and execution for Manipulation - turning hard, contact-rich problems in manufacturing, logistics, and industrial automation into shipping capabilities that our partners and developers can build on. This is a high-visibility role with direct line of sight to the most consequential problems in robotics today. You will grow and mentor a team of world-class robotics and machine-learning engineers, set a bold technical direction, and partner deeply with the robot-arm and industrial-automation ecosystem to make NVIDIA the default platform for robotic manipulation.
What you'll be doing:
Lead the Isaac Manipulation team. Recruit, grow, and mentor a high-performing team of robotics software engineers; set direction, raise the technical bar, and manage the team's health, velocity, and delivery.
Shape the roadmap. Collaborate with Product Management to define and drive the strategy and roadmap for grasping, motion planning and control, perception-for-manipulation, and learned manipulation policies - from research to productized, supported platform capabilities.
Apply creative solutions to real industrial problems. Translate the hardest contact-rich manipulation tasks in manufacturing, logistics, assembly, and machine tending into robust capabilities that work in the real world, not just the lab.
Bridge research and product. Partner with NVIDIA Research, the Isaac Sim/Lab teams, and foundation-model teams (e.g., Isaac GR00T, Cosmos) to bring sim-to-real, imitation, and reinforcement learning approaches into the platform and onto physical arms.
Engage partners and developers. Serve as a technical face of Isaac Manipulation to robot-arm OEMs, system integrators, and the developer community - gathering requirements, running joint engineering, and ensuring our APIs and tools meet real workflows. Support our ecosystem of developers through responsible migration handling of their solutions built on our durable platform.
Leverage accelerated compute. Drive architecture and execution that fully uses NVIDIA GPUs, CUDA, and the accelerated-computing stack across simulation, training, and on-robot inference on Jetson and edge platforms.
Deliver. Drive planning and execution of complex, multi-functional programs; own quality, performance, and the real-world deployment of learned policies and manipulation stacks on physical robots.
Influence the strategy. Represent manipulation in platform-level technical and business decisions, and help shape where NVIDIA invests across the robotics stack.
What we need to see:
BS, MS, or PhD in Robotics, Computer Science, Electrical/Mechanical Engineering, or a related field (or equivalent experience).
12+ total years of relevant industry experience building robotics or robotics-adjacent systems, including 3+ years leading, mentoring, and managing engineering teams.
Robotic arm depth. Hands-on expertise with robotic arms, manipulation, and physics from grasping, motion planning (across both numerical optimization and sampling-based approaches), and control (including force/impedance and contact-rich control) to perception-guided manipulation.
Accelerated compute. Working understanding of GPU-accelerated computing and modern ML infrastructure, and how to architect robotics software to take advantage of it (CUDA, PyTorch, GPU-accelerated simulation, edge inference).
Partner and developer interface. Demonstrated ability to work directly with external partners, customers, and developer communities and to translate their needs into roadmap and shipping product.
Technical credibility. Strong software engineering fundamentals (modern C++ and Python) and the ability to engage substantively in technical and architectural decisions with your team.
Ways to stand out from the crowd:
Industry leadership and fluency. Experience building manipulation or industrial automation products at an established robot-arm company or manipulation startup, and a strong understanding of the product landscape including use cases, the integrators, and the platforms from leading vendors.
Hardware-agnostic platforms. A track record building developer-facing or low-code platforms and tooling that abstract across multiple robot-arm brands and make manipulation accessible to non-experts.
Learned manipulation. Deep experience with imitation learning, reinforcement learning, sim-to-real transfer, or manipulation foundation models, and shipping learned policies onto real hardware.
Ecosystem & OSS. Contributions to ROS 2, ros2_control, MoveIt, or the broader robotics open-source and standards community.
Founder / 0-to-1 instincts. Experience starting or scaling a product or team from the ground up and operating with speed in ambiguous, fast-pace problem spaces.
Manipulation is one of the defining unsolved problems in robotics, and NVIDIA is uniquely positioned - across simulation, foundation models, and accelerated compute - to solve it at platform scale. You'll lead a team that the entire robotics industry builds on, and your work will show up on factory floors and in warehouses around the world!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD for Level 4, and 320,000 USD - 488,750 USD for Level 5.You will also be eligible for equity and benefits.
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.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