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
E-commerce
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
Around the world, leading commercial and academic organizations are using GPUs to redefine AI, scientific and engineering simulations, and data analytics. NVIDIA's GPU-accelerated libraries are used in healthcare, virtual reality, autonomous vehicles, social media, and e-commerce.
In this role, you will join a team responsible for developing libraries that provide groundbreaking functionality and performance. The internship may include extending existing libraries and building new libraries for various AI and high-performance computing applications. You will work with senior software engineers who will provide mentorship and guidance.
The project will include implementing new image and data processing algorithms, defining APIs, analyzing performance, finding appropriate solutions for difficult numerical corner cases, and performing other general software engineering work.
Responsibilities
- Collaborate with team members and other 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.
- Parallel or GPU programming experience with technologies such as AVX, NEON, OpenMP, MPI, CUDA, or OpenCL.
- Experience with image coding, such as JPG and TIFF, or data compression algorithms, such as LZW and 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 widely considered to be one of the technology world's most desirable employers. The company values creative and autonomous people and is an equal opportunity employer that values diversity. NVIDIA does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Internship pay is based on the position, location, year in school, degree, and experience. For Poland, the annual range for interns is 117,750 PLN–204,100 PLN, prorated for the duration of the internship.