System Software Engineer - Performance Lab

at Nvidia

USD 184,000-356,500 per year

MIDDLE SENIOR

✅ On-site

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 Algorithms @ 3 CUDA @ 3 Data Structures @ 3 Deep Learning GPU @ 3 HPC Kubernetes Linux @ 3 Machine Learning @ 3 PyTorch @ 2 Python @ 3 Slurm

Details

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment.

We are looking for you to join NVIDIA’s Performance Lab where you will be encouraged to craft and build outstanding software solutions that challenge NVIDIA products in new ways. Our team values passion and positive interactions with teammates, and offers the opportunity to work on cutting edge technologies in AI, Graphics Rendering, and Datacenters.

Responsibilities

Writing and maintaining containerized GPU accelerated workloads for the financial services industry, from deep learning training and inference, to portfolio optimization and backtesting.
Running, validating, and analyzing benchmarking models at scale on HPC clusters.
Visualizing performance data, building charts and dashboards using internal schemas and tooling.
Working closely with the latest and greatest in financial AI models and tooling to help build reference models for NVIDIA.

Requirements

Bachelor’s degree in Computer Engineering, Software Engineering, Computer Science, or related field (or equivalent experience) with 8+ years of experience.
Desire to improve code quality by learning and applying computer science fundamentals, algorithms, and data structures.
Comfort with teamwork, collaboration, and a desire to reach across functional borders to develop new partnerships.
Professional experience with Python.
Working comfort in a Linux command-line environment with version control.
Foundational understanding and interest of the machine learning lifecycle (training, evaluation, and inference).

Ways to stand out from the crowd

Familiarity with PyTorch and/or training, testing, and evaluating machine learning models.
Experience with GPU computing or CUDA and libraries like 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.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. You will also be eligible for equity and benefits.