Jobs in China

What you’ll be doing:

• Develop and test deep learning models for object detection, tracking, and behavior prediction.

• Preprocess and analyze sensor data from LiDAR, radar, and camera systems.

• Collaborate with cross-functional teams on algorithm integration and performance evaluation.

• Support data labeling, simulation, and validation pipelines.

• Document model performance and contribute to internal reports.

What we need to see:

• Enrolled in a Bachelor’s, Master’s, or PhD program in Computer Science, Electrical Engineering, Robotics, or a related field.

• Strong knowledge of Python and libraries such as PyTorch or TensorFlow.

• Familiarity with computer vision, deep learning, and reinforcement learning concepts.

• Experience with autonomous systems, robotics, or simulation tools a plus.

• Internship duration: 10–12 weeks (with potential for extension)

• Keeping track of the latest developments in NVIDIA technology and build demos for regional colleagues outreached activities.

• Assist the team engaging AI community and collaborator through Accelerated AI workshop.

• Develop demonstration using NVIDIA SDKs e.g., RIVA, Merlin, NeMo, TensorRT, Maxine, Triton Inference Server, etc

• Algorithmic development and experimentation on machine learning project

• AI Software development

• Pursuing BS, MS or PhD in Computer Science, Data Science, Mathematics, or a related field.

• Experience with machine learning and / or deep learning

• Excellent oral and written communication skills in English.

• Familiar with Linux OS environment

• Python Programming

What you’ll be doing:

• Analyze state of the art DL networks (LLM etc.), identify and prototype performance opportunities to influence SW and Architecture team for NVIDIA's current and next gen inference products.

• Develop analytical models for the state of the art deep learning networks and algorithm to innovate processor and system architectures design for performance and efficiency.

• Specify hardware/software configurations and metrics to analyze performance, power, and accuracy in existing and future uni-processor and multiprocessor configurations.

• Collaborate across the company to guide the direction of next-gen deep learning HW/SW by working with architecture, software, and product teams.

What we need to see:

• BS or higher degree in a relevant technical field (CS, EE, CE, Math, etc.).

• Strong programming skills in Python, C, C++.

• Strong background in computer architecture.

• Experience with performance modeling, architecture simulation, profiling, and analysis.

• Prior experience with LLM or generative AI algorithms.

Ways to stand out from the crowd:

• GPU Computing and parallel programming models such as CUDA and OpenCL.

• Architecture of or workload analysis on other deep learning accelerators.

• Deep neural network training, inference and optimization in leading frameworks (e.g. Pytorch, TensorRT-LLM, vLLM, etc.).

• Open-sourceAIcompilers (OpenAI Triton, MLIR, TVM, XLA, etc.).

You will be part of global Performance Lab team, improving our capacity to expertly and accurately benchmark state-of-the-art datacenter applications and products. We also work to develop infrastructures and solutions that enhance the team’s ability to gather data through automation and designing efficient processes for testing a wide variety of applications and hardware. The data that we collect drives marketing/sales collaterals as well as engineering studies for future products. You will have the opportunity to work with multi-functional teams and in a dynamic environment where multiple projects will be active at once and priorities may shift frequently.

What you’ll be doing:

• Benchmark, profile, and analyze the performance of AI workloads specifically tailored for large-scale LLM training and inference, as well as High-Performance Computing (HPC) on NVIDIA supercomputers and distributed systems.

• Aggregate and produce written reports with the testing data for internal sales, marketing, SW, and HW teams.

• Develop Python scripts to automate the testing of various applications.

• Collaborate with internal teams to debug and improve performance issues.

• Assist with the development of tools and processes that improve our ability to perform automated testing.

• Setup and configure systems with appropriate hardware and software to run benchmarks.

What we need to see:

• Currently pursuing a bachelor's degree (or higher) in Computer Science, Electrical Engineering, or a related field.

• Experienced in programming and debugging with scripting languages such as Python or Unix shell.

• Strong data analysis skills and the ability to summarize findings in a written report.

• Hands-on experience with Linux based systems. Familiarity using a container platform such as Docker or Singularity. Experience with compiling and running software from source code.

• Good English verbal and written skills to improve collaboration with coworkers.

• Fast and self-learning capabilities.

Ways to stand out from the crowd:

• Experience with CI/CD pipelines and modern DevOps practices. Familiar with cloud provisioning and scheduling tools (Kubernetes, SLURM).

• Curiosity about GPUs, TPUs, cloud and performance benchmarking.

• Familiar with ML/DL techniques, algorithms and frameworks like TensorFlow or PyTorch. Experience in AI model inference deployment and training launching.

• Background of system-level problem solving.

What you’ll be doing:

• Drive the implementation and deployment of NVIDIA Inference Microservice (NIM) solutions

• Use NVIDIA NIM Factory Pipeline to package optimized models (including LLM, VLM, Retriever, CV, OCR, etc.) into containers providing standardized API access for on-prem or cloud deployment

• Refine NIM tools for the community, help the community to build their performant NIMs

• Design and implement agentic AI tailored to customer business scenarios using NIMs

• Deliver technical projects, demos and client support tasks as directed by the Solution Architecture Leadership

• Provide technical support and guidance to customers, facilitating the adoption and implementation of NVIDIA technologies and products

• Collaborate with cross-functional teams to enhance and expand our AI solutions portfolio

• Be an internal champion for NVIDIA software and total solutions in technical community

• Be an industry thought leader on integrating NVIDIA technology especially inference services into LHA, business partners and whole community

• Assist in supporting NVAIE team and driving NVAIE business in China

What we need to see:

• 3+ years working experience with Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field

• Proven experience in deploying and optimizing large language models

• Proficiency in at least one inference framework (e.g., TensorRT, ONNX Runtime, PyTorch)

• Strong programming skills in Python or C++

• Familiarity with main stream inference engines (e.g., vLLM, SGLang)

• Experience with DevOps/MLOps such as Docker, Git, and CI/CD practices

• Excellent problem-solving skills and ability to troubleshoot complex technical issues

• Demonstrated ability to collaborate effectively across diverse, global teams, adapting communication styles while maintaining clear, constructive professional interactions

Ways to stand out from the crowd:

• Experience in architectural design for field LLM projects

• Expertise in model optimization techniques, particularly using TensorRT

• Knowledge of AI workflow design and implementation, experience on cluster resource management tools. Familiarity with agile development methodologies

• CUDA optimization experience, extensive experience designing and deploying large scale HPC and enterprise computing systems

What you’ll be doing:

• Research, design, and develop architecture solutions of NVIDIA’s accelerating processor
• Work on Deep-Learning architecture, algorithms, and software development
• Developfunction/performance/powermodels for NVDLA
• Co-work with other teams to deliver high quality Deep-Learning processors

What we need to see:

• MS degree from EE/CS or related majors from a prestigious university.
• Experience in C/C++/Python/SystemC
• Proficient in English reading and writing.
• Self-motivated, good teammate.

Ways to stand out from the crowd:

• Ability to work independently as well as in a multi-disciplinary group environment
• Mastery in Compute Vision, Processor architecture, Pattern recognition/machine learning is a plus
• Hardware design or Deep Learning background is a plus.

What you’ll be doing:

• Algorithm and architecture study of display solutions
• Modeling of Display IP

What we need to see:

• Pursuing Master candidate in EE/CS or related field
• Basic C/C++ knowledge is a must

Ways to stand out from the crowd:

• Quick learner, willing to take challenges in a new field
• DP/HDMI background is a plus
• Digital circuit knowledge is a plus