Are you looking to be part of a fun, creative company at the forefront of groundbreaking technologies? NVIDIA is leading the way in some of the world's most exciting tech areas, including Virtual Reality, Artificial Intelligence, Deep Learning, and Autonomous Vehicles. We are widely recognized as one of the most desirable employers, with some of the most forward-thinking individuals in the industry working with us. There has never been a more exciting time to join our team!

We are looking for a passionate and dedicated System Solution Verification and Replay Engineering Intern to join our Autonomous Vehicles team. In this role, you will have the opportunity to delve into cutting-edge autonomous driving full stack technology, focusing on building the NDAS end-to-end functionality KPI verification workflow. This is an excellent opportunity to gain hands-on experience in the field of autonomous driving and work with cutting-edge technology.

What You Will Be Doing:

• Develop and implement the NDAS end-to-end functionality KPI verification workflow.

• Collaborate with the NDAS Test Engineering team to integrate highly automated simulation and Replay KPI workflows.

• Participate in in-vehicle test drives and perform deep analysis on the recorded data.

• Select appropriate datasets based on business requirements, process data, and write accurate evaluators to obtain correct end-to-end KPIs.

• Work closely with developers and operational teams to understand their needs and improve the scalability and stability of the workflow.

• Proactively explore and optimize existing solutions to enhance simulation system performance and reliability.

What We Need to See:

• Availability to work 4 days a week for at least 4 months.

• Master’s or Ph.D. degree in Computer Science, Robotics, Automotive Engineering, Electrical Engineering, Mechanical Engineering, or a related field.

• Strong analytical and problem-solving skills with attention to detail.

• Strong knowledge of programming and debugging techniques, proficiency in C++ and Python.

• Good understanding of autonomous driving system frameworks and software stack.

• Ability to adapt to fast-paced development lifecycles and multi-functional organizations.

• Strong teamwork spirit and excellent communication skills.

• Strong self-motivation and the ability to work independently to explore and optimize existing solutions.

Ways to Stand Out from the Crowd:

• Prior experience with in-vehicle testing, simulation, and metrics development for autonomous driving systems.

• Knowledge of various OS environments such as Linux, QNX, or Real-time operating systems.

• Hands-on experience with NVIDIA DRIVE platform.

• Familiarity with various automotive sensors like Radar, Lidar, and Cameras.