Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
C @ 3
C++ @ 3
CUDA @ 3
Computer Vision
Data Structures
Deep Learning
Linux @ 3
OpenGL @ 3
PyTorch @ 3
Python @ 3
Robotics
TensorFlow @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA is seeking strategic, ambitious, hardworking, and creative students for 12-week, full-time internships with its Autonomous Vehicles and Robotics teams. Interns will work on projects with a measurable impact on the business and gain hands-on experience with NVIDIA technologies. Applications are reviewed on an ongoing basis.
Responsibilities
Autonomous Vehicles
- Develop and train state-of-the-art deep neural networks for path generation.
- Collect training datasets and real-time inference runtimes using simulators and gyms.
- Perform in-vehicle testing.
- Potential focus areas include computer vision, mapping, localization, SLAM, and image processing and segmentation.
Robotics
- Build fundamental infrastructure and software platforms at the core of the system powering robots and applications built with Isaac.
- Potential focus areas include robotics, autonomous vehicles, validation frameworks for deep learning, operating systems, data structures, physics simulation, simulators, computer graphics, version control, computer vision, and cloud technologies.
Requirements
- Must be actively enrolled in a university and pursuing a B.S., M.S., or Ph.D. degree in Electrical Engineering, Computer Engineering, or a related field for the full duration of the internship.
- The anticipated graduation month and year must be clearly indicated on the resume or CV.
- Depending on the internship role, prior experience or knowledge may be required in C, C++, C++17, CUDA, ROS, Python, OpenGL, Linux, sensor input devices such as LiDAR, cameras, and radars, and training frameworks such as TensorFlow, Keras, and PyTorch.
Internship Details
- Duration: 12 weeks
- Schedule: Full time
- Applications are accepted on an ongoing basis.
- This posting is for an existing vacancy.
Benefits
Interns are eligible for NVIDIA intern benefits. NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer.
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