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Listed location: Canada, Remote | Canada, Toronto
Work arrangement: remote. A remote label does not confirm worldwide eligibility or visa sponsorship.
Read the employer’s description for qualifications, compensation and work eligibility. Confirm the position is still open on the application page.
Job description supplied by NVIDIA; category and skill labels may be inferred. How our listings work · Report a problem
Job Description
Join a team of engineers at NVIDIA dedicated to scaling the AI infrastructure that powers cutting-edge data science applications. Our team solves complex challenges across datacenter hardware, networking, distributed systems, and software deployment. We collaborate closely to design and deliver leading infrastructure solutions. We value strong technical foundations paired with creative thinking and a bias toward execution. Together, we continuously push boundaries, grow our skills, and advance NVIDIA’s capacity to build and deploy AI-based infrastructure at scale.
What you will be doing:
- Contribute to a comprehensive platform that automates GPU asset provisioning, configuration, and lifecycle management across cloud providers.
- Build end-to-end automation of data center management, break/fix, and the full span of system upkeep for large-scale Machine Learning systems.
- Implement monitoring and health management capabilities that enable industry-leading reliability, availability, and scalability of GPU assets.
- Harness multiple data streams, ranging from GPU hardware diagnostics to cluster and network telemetry.
- Build automated test infrastructure that we use to qualify distributed systems for operation.
- Partner with engineering teams across NVIDIA to ensure the software integrates seamlessly from the hardware all the way up to the AI training applications.
What we need to see:
- 5+ years of experience in a similar role working on large-scale production systems.
- BS in Computer Science/Engineering/Physics/Mathematics or other comparable degree, or equivalent experience.
- Expert level knowledge of a systems programming language (Go, Python, and/or Rust) and a solid understanding of Data Structures and Algorithms.
- Strong background in Linux system administration and management.
- Deep knowledge of container orchestration platforms such as Kubernetes and/or SLURM.
- Understanding of performance, security, and reliability in complex distributed systems.
- Familiarity with system level architecture, data synchronization, fault tolerance, and state management.
Ways to stand out from the crowd:
- Proficiency in designing and building widespread distributed networks.
- Experience managing large-scale distributed systems independently of cloud providers.
- Extensive expertise in datacenter operations and GPU hardware.
- Hands-on experience working with RDMA networking.
- Advanced hands-on experience and deep understanding of cluster management systems (Kubernetes, SLURM).
135,000 CAD – 185,000 CAD for Level 3; and 170,000 CAD – 220,000 CAD for Level 4.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
Skills mentioned
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Frequently asked questions
Is the Senior Software Engineer - DGX Cloud position at NVIDIA remote?
Yes. The Senior Software Engineer - DGX Cloud role at NVIDIA is a remote position. Country eligibility is not specified here; check the employer listing.
What type of employment is the Senior Software Engineer - DGX Cloud role?
NVIDIA is hiring for a full-time Senior Software Engineer - DGX Cloud position.
Which skills are mentioned for the Senior Software Engineer - DGX Cloud job at NVIDIA?
Detected skill labels include Python, Kubernetes, Go, Rust, Distributed Systems, GPU. Check the employer description to distinguish required skills from preferred experience.
How do I apply for the Senior Software Engineer - DGX Cloud position at NVIDIA?
You can apply for the Senior Software Engineer - DGX Cloud role directly through NVIDIA's official application link provided on this page.
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