Role at a glance
- Salary
- $152K – $287.5K/yr
- Location
- 2 Locations, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 5+ years of hands-on experience in embedded systems
- Education
- BS in Electrical Engineering, Computer Engineering, Computer Science, Robotics, Mechanical Engineering, or a related field (or...
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Role Summary
The Solutions Architect serves as the primary embedded systems expert for NVIDIA’s Physical AI partners, working across hardware bring-up, sensor integration, and deployment of robotics models. The role bridges NVIDIA Engineering, Product, Sales, Ecosystem teams, and customers to turn prototypes into production-grade, AI-accelerated robotics systems.
What You'll Do
- Engage with customers to integrate production stacks including real-time Linux environments, ROS 2, sensor pipelines, and edge AI models.
- Deploy, profile, and optimize robotics foundation models on embedded computers and guide customers on tradeoffs.
- Translate customer requirements into NVIDIA-based architectures and feed field insights into product feedback and roadmap priorities.
- Lead technical discussions, presentations, and hands-on workshops with key partners.
- Develop proof-of-concepts and reference implementations.
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View full postingQualifications
Bachelor’s degree or equivalent experience; 5+ years of hands-on embedded systems experience; fluency in ROS 2; experience with sensor pipelines and AI model deployment, optimization, and GPU profiling on edge hardware.
Required
- BS in Electrical Engineering, Computer Engineering, Computer Science, Robotics, Mechanical Engineering, or a related field (or...
- 5+ years of hands-on experience in embedded systems, including developing on NVIDIA Jetson, performance tuning, and system-level debugging
- Strong fluency in ROS 2 and background in deploying robotics autonomy stacks and sim-to-real validation workflows
- Previous work integrating sensor pipelines such as cameras, LiDAR, and IMU
- Proven expertise in AI model deployment, optimization, and GPU profiling on edge hardware, using SDKs like TensorRT
- Outstanding communication and collaboration skills
Preferred
- Hands-on experience with NVIDIA Robotics libraries such as Isaac ROS and cuVSLAM, as well as simulation frameworks like Isaac Sim and...
- Familiarity with deploying and optimizing VLMs, VLAs such as GR00T, or World Models such as Cosmos on edge platforms
- Experience with camera and sensor software stacks such as NVIDIA’s HSB, V4L2, GMSL cameras, ISP tuning, or high-throughput video processing
- Prior experience with real-time and safety-aware embedded robotics systems in industries like autonomous vehicles or manufacturing
- Experience using agentic tooling to accelerate integration, debug, and build reference-implementation work
Original job description
Content provided by the employer
Original job description
Content provided by the employer
Physical AI is redefining what robots can do, and embedded platforms are where that future becomes real! We are looking for a hands-on Solutions Architect with deep embedded systems expertise to serve as a technical anchor for NVIDIA’s Physical AI ecosystem. This role sits at the intersection of hardware bring-up, sensor integration, and deployment of next-generation robotics models. You will bridge pioneering research and real-world application engineering, working closely with customers and NVIDIA Engineering, Product, Sales, and Ecosystem teams to turn prototypes into production-grade, AI-accelerated robotics systems.
Are you are passionate about Robotics and ready to make a meaningful difference? If so, this role fits you!
What you'll be doing:
Serve as the primary embedded systems expert for NVIDIA Physical AI partners using technologies such as Jetson, Holoscan, Isaac ROS, Isaac OS, GR00T.
Engage with customers to ensure smooth integration of production stacks, including real-time Linux environments, ROS 2, sensor pipelines, and edge AI models.
Deploy, profile, and optimize robotics foundation models (VLAs, World Models) on embedded computers and guide customers on tradeoffs
Translate customer requirements into practical NVIDIA-based architectures, and work closely with internal teams to feed field insights into product feedback and roadmap priorities.
Lead technical discussions, presentations, and hands-on workshops with key partners, while developing proof-of-concepts, and reference implementations.
What we need to see:
BS in Electrical Engineering, Computer Engineering, Computer Science, Robotics, Mechanical Engineering, or a related field (or equivalent experience).
5+ years of hands-on experience in embedded systems, including developing on NVIDIA Jetson, performance tuning, and system-level debugging.
Strong fluency in ROS 2 and background in deploying robotics autonomy stacks, and sim-to-real validation workflows.
Previous work integrating sensor pipelines such as cameras, LiDAR, and IMU
Proven expertise in AI model deployment, optimization, and GPU profiling on edge hardware, using SDKs like TensorRT
Outstanding communication and collaboration skills, with the ability to translate complex technical concepts for researchers, engineers, and business teams.
Ways to stand out from the crowd:
Hands-on experience with NVIDIA Robotics libraries such as Isaac ROS and cuVSLAM, as well as simulation frameworks like Isaac Sim and Isaac Lab
Familiarity with deploying and optimizing VLMs, VLAs (such as GR00T) or World Models (such as Cosmos) on edge platforms, including techniques like quantization, compression, and distillation.
Experience with camera and sensor software stacks such as NVIDIA’s HSB (Holoscan Sensor Bridge), V4L2, GMSL cameras, ISP tuning, or high-throughput video processing.
Prior experience with real-time and safety-aware embedded robotics systems in industries like autonomous vehicles or manufacturing.
Experience using agentic tooling to accelerate integration, debug, and build reference-implementation work.
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 the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.