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Salary
$38k – $82k per year (Estimated)
Location
In office (Shanghai)
Seniority
Senior · 5+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
NVIDIA is an American technology company founded in 1993 that invented the graphics processing unit and has become the dominant supplier of accelerated computing platforms for artificial intelligence. Its portfolio spans data centre GPUs and systems built on the Hopper and Blackwell architectures, GeForce consumer graphics, automotive and robotics platforms, high-speed networking acquired with Mellanox, and the CUDA software stack that binds the ecosystem together. Headquartered in Santa Clara, California, the company sells to cloud providers, enterprises, research institutions and gamers worldwide and is one of the most valuable listed businesses on the Nasdaq.

We're seeking a highly technical and hands-on Technical Marketing Engineer to help drive NVIDIA's Robotics and Physical AI initiatives in China. You will work closely with engineering, product, sales, and marketing teams, as well as leading robotics developers, OEMs, and ecosystem partners to evaluate our technologies, improve developer experience, and support adoption of NVIDIA robotics solutions.

China is one of the world's most advanced and fast-moving robotics ecosystems. You will work closely with internal and external stakeholders to understand real-world requirements, emerging use cases, developer needs, and help translate these insights into product feedback, technical guidance, and improved solutions.

You should be comfortable working in a multifaceted environment and possess excellent written and verbal communication skills. The ability to work independently and the motivation to learn new technologies and skills are essential.

What you'll be doing:

  • Own and lead the development of high-impact technical marketing content that clearly articulates the value and differentiation of NVIDIA robotics platforms.

  • Evaluate developer experience, performance, and end-to-end robotics workflows through hands-on testing, benchmarking, debugging, and validation, and provide actionable feedback to engineering and product teams.

  • Work with internal teams and robotics ecosystem partners to understand technical requirements, use cases, and development challenges to help improve NVIDIA robotics solutions.

  • Develop and validate technical demos, reference implementations, benchmarks, and workflows on Physical AI platforms.

  • Collaborate across engineering, research, product, sales, marketing, and solution architecture teams driving strategic alignment and ensuring bi-directional content sharing.

  • Drive technical demos and discussions of our products and technologies at prominent conferences, events, and briefings.

What we need to see:

  • MS degree in Computer Science, Electrical Engineering, or a related technical discipline.

  • 5+ years of hands-on software and/or hardware development experience in robotics, AI, autonomous machines, or related fields.

  • Proven expertise in robotics workflows either in robotics design, simulation, deployment or supporting robotics solutions in real-world environments.

  • Strong C/C++ and Python programming skills, with hands-on Linux development, integration, and debugging experience.

  • Experience with robotics development technologies such as ROS/ROS 2, robotics simulation, and Sim-to-Real workflows.

  • Strong analytical, problem-solving, and communication skills in both English and Mandarin Chinese.

Ways to stand out from the crowd:

  • Hands-on experience with conventional simulation (e.g. NVIDIA Isaac Sim, Isaac Lab) and neural simulation (e.g. Cosmos)

  • Hands-on experience with deployment technologies likeIsaac ROS, Holoscan, Jetson, or other NVIDIA robotics and edge AI technologies.

  • Experience integrating and deploying software on physical robot platforms.

  • Familiarity with leading robotics OEMs, developers, and the robotics ecosystem in China.

  • Experience with advanced robotics technologies such as robotics foundation models, robot learning methodologies, synthetic data generation, real2sim, sim2real, or other robot development workflows.

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