NVIDIAAI Developer Technology Engineer
NVIDIA is hiring an AI Developer Technology Engineer in Shanghai, China. Level rates it ; you can apply on Level.
AI in this role
Optimize and scale embodied AI workloads and simulation frameworks for robotics developers on NVIDIA platforms.
NVIDIA is the engine of modern AI. For over 25 years our work in accelerated computing has redefined computer graphics, autonomous machines, and now physical AI. We are looking for an AI Developer Technology Engineer to join our DevTech team in China. this role you will work directly with the developers and researchers building the next generation of robots, helping them get the most out of NVIDIA GPUs across simulation, training, and deployment. You will be part of an exceptionally experienced, globally distributed team dedicated to pushing the boundaries of embodied AI.
What you’ll be doing
- Partner with leading robotics developers and research teams in China to design, optimize, and scale embodied AI workloads on NVIDIA platforms
- Develop on and extend frameworks such as Isaac Lab, Megatron Core and VLM/VLA/WA inference framework, ensuring flawless performance at scale
- Profile and optimize GPU-based physics simulation, robot foundation model training and inference pipelines; drive the findings back into our products
- Build reference workflows and samples for imitation learning, reinforcement learning, and VLA/WA/VLM model training/inference
- Discuss your approach and results with NVIDIA engineers and external developers to continuously improve processes
- Collaborate closely with architecture, research, libraries, tools, and system software teams to invent and develop next-generation architectures, software platforms, and programming models
- Represent NVIDIA technically at developer events, workshops, and customer engagements in the region
What we need to see:
- Bachelor's degree in Computer Science, Robotics, Engineering, or a related field, or equivalent experience.
- 3+ working year experience.
- Experience with C++, CUDA, Python, and Linux.
- Proven experience with one or more physics simulators such as MuJoCo, Isaac Sim, PyBullet, Drake, or Gazebo.
- Strong communication skills and the ambition to grow and learn about building machine learning applications, optimization, and software engineering.
- Prior involvement with embodied AI or a history at humanoid robotics firms with a focus on physics simulation.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package.Are you a creative and autonomous computer scientist with a real passion for parallel computing? If so, we want to hear from you.
How we rate this
AI Developer Technology Engineer at NVIDIA rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where robotics was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where reinforcement learning was part of your work. What did you do?
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- Tell me about a project where gpu optimization was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Robotics, Machine learning, Reinforcement learning, Computer vision, and GPU Optimization. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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