We are seeking hands-on Mechanical Engineer in Solutions Architecture Team to support the design and development of robotic hardware systems, with a focus on mechanism design and mechatronics integration. This role will contribute to rapid prototyping, iteration, and validation of mechanical subsystems, particularly for end-effectors and robotic assemblies. You’ll collaborate with Gear Lab Team known for influential work in multimodal foundation models, large-scale robot learning, embodied AI, and physics simulation, pushing the frontier of humanoid robotics.
What you'll be doing:
Design and develop mechanical components and assemblies for robotic systems, with emphasis on mechanisms and transmissions
Contribute to end-effector and gripper design, including kinematics, packaging, and integration with actuators and sensors
Prototype and iterate designs using rapid fabrication methods (3D printing, off-the-shelf components, vendor-fabricated parts)
Collaborate with electrical and software engineers to integrate motors, sensors, and control systems
Perform basic analysis and validation of designs (tolerance, strength, failure modes, etc.)
Generate clear CAD models, drawings, and documentation for fabrication and assembly
Support lab build, test, and debugging of hardware systems
What we need to see:
Bachelor’s or Master’s degree in Mechanical Engineering or related field with over 4 years' working experience
Strong fundamentals in mechanical design, including mechanisms, linkages, gear trains, and actuation systems
Experience with robotic systems, mechatronics, or precision mechanical design
Proficiency in CAD (e.g., Onshape, SolidWorks, Fusion 360, or similar)
Familiarity with motors, transmissions, and basic control concepts
Understanding of design for manufacturing (DFM) and tolerance stack-up
Hands-on experience building and debugging physical hardware
Ways to stand out from the crowd:
Experience with end-effectors or gripper design
Familiarity with cable-driven systems, compliant mechanisms, or underactuated designs
Experience working with vendors for CNC, sheet metal, or additive manufacturing
Exposure to sensors (encoders, force/torque, tactile) and their integration
Basic programming or scripting for testing and data collection
Skills Required
- Bachelor's or Master's degree in Mechanical Engineering or related field
- Over 4 years' working experience in mechanical design
- Strong fundamentals in mechanical design, including mechanisms and actuation systems
- Experience with robotic systems or mechatronics
- Proficiency in CAD software
- Hands-on experience building and debugging physical hardware
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
-
Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
-
Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
-
Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
