Drive Sdk Intern Autonomous Driving - jobs at Nvidia in China, Beijing

What you will be doing:

• Investigate and resolve sensor calibration and egomotion algorithm/toolchain issues across multiple OEM vehicle platforms.

• Develop core autonomous driving functionality for global markets by fusing state-of-the-art perception DNNs with map signals.

• Build real-time 3D world models for planning, integrating diverse inputs from sensors and external sources.

• Develop and optimize LLM, VLM, and VLA systems for autonomous driving applications, including pre-training and fine-tuning.

• Design innovative data generation and collection strategies to improve dataset diversity and quality.

• Collaborate with cross-functional teams to deploy end-to-end AI models in production, ensuring performance, safety, and reliability standards are met.

What we need to see:

• A MS, or PhD, or equivalent professional experience in Computer Science, Computer Engineering, Mathematics, Physics, or a related discipline.

• Over 3 years of relevant industry experience.

• Expertise in C/C++ programming, with a comprehensive understanding of standard C++ features, algorithms, and data structures, along with proficiency in Linux environments.

• In-depth knowledge of parameter models for sensor calibration.

• A solid grasp of digital image processing, three-dimensional multi-view geometry, nonlinear optimization, and KF/EKF.

• A robust mathematical foundation, especially in matrix-related concepts.

• Engineering expertise in developing and delivering deep learning applications for autonomous vehicles or robotics

• Engineering expertise in developing and delivering real-time 3D world models for planning in AV system.

• Excellent collaboration skills and the ability to work effectively with individuals from various nationalities and locations.

Ways to stand out from the crowd:

• Experience with a range of sensors and their data (camera, lidar, radar, IMU, GNSS, CAN Odometry).

• Extensive experience in SLAM algorithms

• Extensive deep learning experience related to autonomous driving.

• A track record of designing SLAM algorithms for successful ADAS projects.

What you will be doing:

• You will work and develop state of the art techniques in deep learning, graphs, machine learning, and data analytics, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures

• You will provide the best AI solutions using GPUs working directly with key customers

• Collaborate closely with the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and programming models

What we need to see:

• Pursuing MS or PhD from a leading University in an engineering or Computer Science related discipline

• Strong knowledge of C/C++, software design, programming techniques, and AI algorithms

• Experience with parallel programming, ideally CUDA C/C++

• Good communication and organization skills, with a logical approach to problem solving, time management, and task prioritization skills

Preferred internship duration: 4+ months

We’re working on the next generation of recommendation tools and pushing the boundaries of accelerating model training and inference on GPU. You’ll join a team of ML, HPC and Software Engineers and Applied Researcher developing a framework designed to make the productization of GPU-based recommender systems as simple and fast as possible.

What you’ll be doing

In your role as CUDA Engineer Intern you will be profiling and investigating the performance of optimized code together within our HPC team. Part of this job will be to perform tests, unit tests and validate the numerical performance and correctness of the code. You will discuss your approach and results together with our CUDA engineers.

What we need to see:

• Experience with c++, CUDA, python and Linux.

• Bachelor or Master degree in software engineering or technical field such as mathematics or applied science.

• communication skills

• ambitious to grow and learn about building machine learning applications, optimization and software engineering.

What you will be doing:

• Work and develop state of the art techniques in deep learning, graphs, machine learning, and data analytics, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures

• You will provide the best AI solutions using GPUs working directly with key customers

• Collaborate closely with the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and programming models

What we need to see:

• Available to work as intern for at least 3 months+, 3 days per week

• Pursuing MS or PhD from a leading University in an Engineering or Computer Science related discipline and will graduate in 2027

• Strong knowledge of C/C++, software design, programming techniques, and AI algorithms

• Experience with parallel programming, ideally CUDA C/C++

• Good communication and organization skills, with a logical approach to problem solving, time management, and task prioritization skills

As a member of the team, you will be a part of cutting edge Python-based SW project using advanced techniques such as white box testing, multi-thread environment and more. You will gain unique knowledge of how switch operating system works and how large scale networks are constructed. Teams utilize the latest software engineering methodologies and tools in an agile fashion to release on time. Are you ready for this challenge?

What you will be doing:

• Design, develop, optimize and maintain APIs, tools and libraries for OS Verification infrastructure software

• Collaborate with team members, Architects, design, QA teams, and customers (both external and internal)

• Design, develop, execute and maintain tests automation for release features.

What we need to see:

• Education: computer science or similar, bachelor degree or above

• 4+ years of working experience within networking SW industry

• Computer Network proven experience Layer-2 and Layer-3

• Strong and proven experience with object oriented programming languages

• Strong technical abilities, problem solving, design, coding and debugging skills

• Ability to lead feature development, take full ownership of tasks from A-Z and deliver independently with minimum supervision

• Great teammate with multi-tasking ability and good interpersonal skills

Ways to stand out from the crowd:

• Experienced in C and Python programming

• Knowledge in Networking protocols

What You’ll Be Doing:

• Design and train innovative large-scale models—including generative, imitation, and reinforcement learning—to enhance the planning and reasoning capabilities of our driving systems.

• Build, pre-train, and fine-tune LLM/VLM/VLA systems for deployment in real-world autonomous driving and robotics applications.

• Explore novel data generation and collection strategies to improve diversity and quality of training datasets.

• Collaborate with cross-functional teams to deploy AI models in production environments, ensuring performance, safety, and reliability standards are met.

• Integrate machine learning models directly with vehicle firmware to deliver production-quality, safety-critical software.

What We Need to See:

• 5+ years of experience in developing software infrastructure for large scale AI systems.

• Bachelor's degree or higher in Computer Science or a related technical field (or equivalent experience).

• Hands-on experience building LLMs, VLMs, or VLAs from scratch or a proven track record as a top-tier coder passionate about autonomous systems.

• Deep understanding of modern deep learning architectures and optimization techniques.

• Proven record of deploying production-grade ML models for self-driving, robotics, or related fields at scale.

• Strong programming skills in Python and proficiency with major deep learning frameworks.

• Familiarity with C++ for model deployment and integration in safety-critical systems.

Ways to Stand Out from the Crowd:

• Experience with LLM/VLM/VLA systems deployable to autonomous vehicles or general robotics. Or publications, open-source contributions, or competition wins related to this field.

• Deep understanding of behavior and motion planning in real-world AV applications.

• Experience building and training large-scale datasets and models.

• Proven ability to optimize algorithms for real-time performance in resource-constrained environments.

• Strong track record of taking projects from concept to production deployment.