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Location
Remote (Canada)
Seniority
Senior · 5+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 3, 2026. First seen by Alion on Nov 2, 2026. NVIDIA scores B on the Alion truth index.

Overview
Company
Impact
Profile match
NVIDIA is an American technology company founded in 1993 that invented the graphics processing unit and has become the dominant supplier of accelerated computing platforms for artificial intelligence. Its portfolio spans data centre GPUs and systems built on the Hopper and Blackwell architectures, GeForce consumer graphics, automotive and robotics platforms, high-speed networking acquired with Mellanox, and the CUDA software stack that binds the ecosystem together. Headquartered in Santa Clara, California, the company sells to cloud providers, enterprises, research institutions and gamers worldwide and is one of the most valuable listed businesses on the Nasdaq.

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).

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 6, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

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