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.
AI
API
Algorithms @ 3
CUDA @ 3
Computer Vision
GPU @ 3
HPC
MPI @ 3
Mathematics @ 3
OpenCL @ 3
Performance Analysis @ 3
Python @ 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
Join a multidisciplinary team developing and improving GPU- and CPU-accelerated software libraries supporting AI, data analytics, image processing, computer vision, and scientific simulations for commercial and academic organizations worldwide.
The internship involves extending existing libraries and building new ones for AI, high-performance computing, and medical applications. You will work with senior software engineers who provide mentorship and guidance. Projects may include implementing image and data processing algorithms, defining APIs, analyzing performance, addressing difficult numerical corner cases, and performing general software engineering work.
Responsibilities
- Collaborate with team members and partners to understand software use cases and requirements.
- Research, analyze, and document state-of-the-art algorithms.
- Develop algorithms for image and data compression and processing.
- Analyze and improve the performance of existing implementations.
Requirements
- Pursuing a degree in Computer Science, Artificial Intelligence, Applied Mathematics, or a related field.
- Programming skills in C/C++ and Python.
- Experience with parallel or GPU programming, including AVX, NEON, OpenMP, MPI, CUDA, or OpenCL.
- Experience with image coding, such as JPEG or TIFF, or data compression algorithms, such as LZW or DEFLATE.
Preferred Qualifications
- Knowledge of image processing algorithms.
- Performance analysis and test design skills.
- Familiarity with floating-point arithmetic internals and numerical error analysis.
NVIDIA is an equal opportunity employer and values diversity. The company does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.