Join NVIDIA's Solution Engineering team that is shaping the future of autonomous machines. Our goal is to build and deploy scalable robotic solutions and enable the next generation of AI robots. Our team is hands-on, passionate about practical results, and values diversity.
You will help craft the application software architecture by working closely with external partners developing on our robotics platform and the collaborations across multiple teams within NVIDIA working on autonomous machines. You will also advance and refine the overall functional capability and quality of our solution, focusing on integration challenges and applying deep analytical skills to tease through the complexity of the system to arrive to effective and optimum solutions.
What you'll be doing:
Build and drive the application architecture internally, with a focus on humanoid robotics, by collaborating closely with architecture and software development teams.
Scale the deployment and integration of robust and performant implementations of new technologies spanning whole body controller and manipulation algorithms into solutions and products.
Integrate hardware and software components efficiently and develop scalable software solutions. Lead profiling, benchmarking and evaluation activities for verification.
Provide deep technical guidance and strategies to resolve functional and system performance issues, working with internal and external partner teams.
Collaborate with our global engineering teams in our US, APAC, and Europe locations to deploy the solution to our customers.
What we need to see:
5+ years of work related experience in software development related to robotics.
Bachelors, Masters or equivalent experience in computer science, robotics, computer engineering, or a related field.
Proven track record in developing software products in the domains of machine learning and reinforcement learning, and hands-on physical robot experience, and/or publishing in robotics conferences (RSS, CoRL, ICRA, IROS, NeurIPS, etc.).
Established proficiency in application development and scalability for autonomous machines, and familiarity with robotics or automotive related middleware frameworks.
Experience with robot simulation platforms and simulation-based reinforcement learning for training and validation of robotic systems, with hands-on experience on sim-to-real transfer of RL policies being a plus.
Proficient in Python and C/C++, with experience in GPU programming or CUDA being a strong plus.
Capable of adapting quickly to new technologies and platforms.
Ability to adapt in a fast paced development lifecycles and multi-functional organizations.
Ways to stand out from the crowd:
Hands-on experience with real-world robotic systems and hardware of humanoid robots or mobile manipulator, particularly in loco-manipulation and dexterous hands manipulation tasks.
Experience with ROS 2, Isaac SIM and Isaac Lab or equivalent
Understanding of NVIDIA Isaac, NVIDIA GPU hardware, and CUDA
Contributions to or ownership of open-source project and mentorship experience.
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.Skills Required
- 5+ years of related software development experience in robotics
- Bachelor’s, master’s degree, or equivalent experience in computer science, robotics, computer engineering, or a related field
- Experience developing software products involving machine learning and reinforcement learning
- Hands-on physical robot experience and/or publications in robotics conferences
- Proficiency in application development and scalability for autonomous machines
- Familiarity with robotics or automotive middleware frameworks
- Experience with robot simulation platforms and simulation-based reinforcement learning for training and validation
- Proficiency in Python and C/C++
- Ability to adapt quickly to new technologies and platforms
- Ability to work in fast-paced development lifecycles and multifunctional organizations
- Experience with real-world humanoid robots or mobile manipulators, including loco-manipulation or dexterous hand manipulation
- Experience with ROS 2, Isaac Sim, Isaac Lab, or equivalent technologies
- Understanding of NVIDIA Isaac, NVIDIA GPU hardware, and CUDA
- Experience with sim-to-real transfer of reinforcement learning policies
- GPU programming or CUDA experience
- Open-source contributions or mentorship experience
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.
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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.
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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.
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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.”
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