Used Tools & Technologies
Not specified
Required Skills & Competences
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.
Kubernetes @ 3
Linux @ 3
Python @ 3
Algorithms @ 3
Data Structures @ 3
Machine Learning @ 3
PyTorch @ 2
CUDA @ 3
GPU @ 3
Deep Learning @ 3
AI @ 3
Slurm @ 3
HPC @ 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 a worldwide technology company headquartered in Santa Clara, California. NVIDIA manufactures graphics processing units (GPUs) and system-on-chip units (SOCs). This internship joins the team responsible for maintenance, development, and execution of Desktop Gaming Performance testing in Linux and Windows environments for GPUs. The role has a preferred duration of 8–12 months.
Responsibilities
- Write and maintain containerized GPU-accelerated workloads for financial services use cases, including deep learning training and inference, portfolio optimization, and backtesting.
- Run, validate, and analyze benchmarking models at scale on HPC clusters.
- Visualize performance data and build charts and dashboards using internal schemas and tooling.
- Work closely with financial AI models and tooling to help build reference models for NVIDIA.
Requirements
- Enrolled in a Bachelor's program in Computer Engineering, Software Engineering, Computer Science, or a related field.
- Desire to improve code quality using computer science fundamentals, algorithms, and data structures.
- Comfortable working in teams and collaborating across functions.
- Active experience with Python.
- Working comfort in a Linux command-line environment with version control.
- Foundational understanding and interest in the machine learning lifecycle (training, evaluation, inference).
Ways to stand out
- Familiarity with PyTorch and/or training, testing, and evaluating machine learning models.
- Experience with GPU computing or CUDA and related libraries (cuOPT, CUTLASS, cuDNN, etc.).
- Exposure to workload orchestration and job schedulers (Kubernetes, Slurm).
- Experience with containerized applications and resource management.
- Interest in quantitative finance and applying performance data to real-world problems.
Compensation and Benefits
- Internship hourly rate: 20 USD - 71 USD.
- Eligible for NVIDIA intern benefits (link provided in original posting).
Additional information
- Applications accepted at least until July 10, 2026.
- This posting is for an existing vacancy. NVIDIA uses AI tools in recruiting processes and is an equal opportunity employer.