
Leading supplier of end-to-end high speed Ethernet and InfiniBand intelligent interconnect solutions and services.

Leading supplier of end-to-end high speed Ethernet and InfiniBand intelligent interconnect solutions and services.
Company: NVIDIA
Core focus: Accelerated computing and AI infrastructure (GPUs, data center and AI systems, edge/robotics, automotive)
Founded: April 1993
Public company / Investor relations: Maintains an active investor relations portal with quarterly results and presentations
High-performance graphics, machine learning/AI acceleration, and full-stack AI infrastructure for enterprise, cloud and edge use cases.
1993
Semiconductors / AI infrastructure
Historical financing and IPO-related information are documented on financial profiles; NVIDIA also deploys strategic investments in startups (examples reported)
$2B
Reported $2B investment to support CoreWeave's AI compute expansion
As NVIDIA makes inroads into the Datacenter business, our team plays a central role in getting the most out of our exponentially growing datacenter deployments as well as establishing a data-driven approach to hardware design and system software development. The role of a Deep Learning Systems Engineer would be to analyze the performance and power consumption of deep learning applications on datacenter-class hardware and significantly influence the design and optimization of datacenters.
Do you want to influence the development of high-performance Datacenters designed for the future of AI? Do you have an interest in system architecture and performance? In this role you will find how CPU, GPU, networking, and IO relate to deep learning (DL) architectures for Natural Language Processing, Computer Vision, Autonomous Driving and other technologies. Come join our team, and bring your interests to help us optimize our next generation systems and Deep Learning Software Stack.
What You'll Be Doing
What We Need To See
Ways To Stand Out From The Crowd
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until September 7, 2025.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
JR2000694
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A Bachelor’s degree in Electrical Engineering or Computer Science or equivalent experience (Masters or PhD degree preferred).
8 years or more of relevant experience.
Experience in at least one of the following:
System Software: Operating Systems (Linux), Compilers, GPU kernels (CUDA), DL Frameworks (PyTorch, TensorFlow).
Silicon Architecture and Performance Modeling/Analysis: CPU, GPU, Memory or Network Architecture
Experience programming in C/C++ and Python. Exposure to Containerization Platforms (docker) and Datacenter Workload Managers (slurm) is a plus.
A deep understanding of computer system architecture and performance analysis is essential for success in this role. Applicants should have demonstrated hands-on experience in these domains.
Demonstrated ability to work in virtual environments, and a strong drive to own tasks from beginning to end. Prior experience with such environments will make you stand out.