- 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.
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 152,000 USD – 241,500 USD for Level 3; and 184,000 USD – 287,500 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.