
DL System Software Engineer - AI Platform
Role summary
NVIDIA is seeking a Systems Engineer to develop an AI Platform for efficient large-scale model training and inference. The role involves designing and building solutions for GPU cluster workload scheduling across cloud infrastructure, addressing challenges in resource management, scheduling, performance prediction, and migration. The engineer will work with NVIDIA technologies and contribute to adjacent teams. A Bachelor's degree or equivalent experience, 5+ years of experience building large-scale systems, strong coding skills in Python, Go, Rust, or C/C++, and a solid foundation in computer science fundamentals are required. Experience with Kubernetes, AI/ML, containerization, and NVIDIA GPU technologies are highly advantageous.
We are seeking highly motivated and skilled systems engineers to join our team to help in developing an AI Platform that offers an efficient infrastructure for inference and training large scale models. As a systems engineer, you will play a crucial role in building a unified solution that brings our innovative NVIDIA technologies such as high-performance, inference/training frameworks, ML compilers, performance predictor, and cluster scheduler into a single, cohesive platform.
What You Will Be Doing
- Taking part in the development of the NVIDIA's AI platform for training, fine-tuning and serving latest and greatest AI models with the best performance and efficiency.
- Designing and building solutions for scheduling large scale AI training and inference workloads on GPU clusters over many cloud infrastructure.
- Exploring and finding solution for open problems like industry-scale resource management, GPU scheduling, performance prediction, and live workload migration.
- Work with and contribute to adjacent teams like TensorRT/Dynamo inference engine, ML compiler, KAI/Grove scheduler, Lepton cloud etc.
What We Need To See
- Bachelor's degree or equivalent experience in Computer Science, Computer Engineering, relevant technical field.
- 5+ years of experience.
- Experience building large scale systems from scratch. Prior experience in container-based deployment systems like Kubernetes is beneficial.
- Strong coding skills in programming languages like Python, Go, Rust and/or C/C++.
- Solid foundation in other computer science and computer engineering topics: algorithms and data structures, operating systems, computer architecture, etc. Strong understanding of AI and related technologies is a huge plus.
- Most importantly, ability to quickly grasp new concepts and thrive in evolving situations.
Ways To Stand Out From The Crowd
- Graduate-level education or relevant practical background, particularly in research, is beneficial.
- Practical experience in building and optimizing AI applications is highly desired.
- Proficiency in container software such as containerd, CRI-O, Linux namespace, CRIU, and NVIDIA GPU technology such as CUDA graphs, Driver/runtime is greatly advantageous.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 135,000 CAD - 185,000 CAD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until March 21, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
, , JR2002456
Sample NVIDIA interview questions
- 1
Design a system for a rock paper scissors game
system designmedium - 2
Implement a distributed data migration management platform.
system designmedium - 3
Develop a distributed tracing system for tracking and debugging.
system designmedium - 4
Design a distributed training system for a trillion-parameter language model
system designmedium - 5
Design a system for an automation framework to generate a consent form using multiple agents
system designaverage
Sign up for a personalized interview prep pack tailored to this role.