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Intern High Performance Computing Engineer Jobs in Toronto, ON

As an Advanced GPU HW Hardware Development Lab Engineer, you will be chiefly responsible for ... While working with cutting edge HPC (high performance computing) technologies, you will be part of ...

Experience working with large-scale data systems, high-performance computing, or cloud-native architectures Preferred Qualifications * Master's or PhD in Computer Science, Engineering, AI, or related ...

Electrical Engineer - Optical & Embedded Systems Status: Full-time Location: Hamilton, ON CANADA ... high-performance computing. You will step into a role defined by technical ownership and end-to-end ...

The Role We are looking for a Product & Test Engineer to drive post-silicon productization of our ... Experience with high-performance computing, AI, networking, or bitcoin mining ASICs.

Are you passionate about pushing the boundaries of power efficiency and high-frequency computing ... Desirable candidates have an MS/PhD degree in Electrical Engineering LOCATION: Austin, TX, Santa ...

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Senior Systems Software Engineer, LPU

Senior Systems Software Engineer, LPU

Nvidia

Toronto, ON • On-site

Full-time

Posted 18 days ago


Job description

NVIDIA's LPU System Software team builds foundational software that enables deterministic, high-performance computing platforms by shifting complexity from silicon into software. We design and maintain the hardware abstraction layers, core system libraries, and runtime components that allow compiler teams and data center operators to safely and efficiently execute workloads on novel architectures. In this role, you will develop and evolve the libraries, drivers, and runtime interfaces that serve as key entry points into the platform. You will also help improve reliability and operability through automation, diagnostics, and tight cross-org collaboration with hardware, compiler, and operations teams.


What you'll be doing:

  • Extend and maintain hardware abstraction layers and core system libraries used across the platform.

  • Design and implement drivers, runtimes, and data movement/aggregation pipelines supportingworkload execution.

  • Build and maintain runtime interfaces for launching, monitoring, and managing workloads.

  • Improve platform reliability through automation, error reporting, diagnostics, and operationaltooling.

  • Debug and resolve complex sequencing, initialization, and runtime issues across multi-componentsystems.

  • Partner cross-functionally with hardware engineering, compiler teams, and data center operationsto bring features from prototype to production.

  • Support new platform bring-up and NPI (New Product Introduction) efforts for new boards andsilicon.

  • Contribute to engineering excellence through documentation, tooling improvements, code reviews,and knowledge sharing.

What we need to see:

  • A Masters Degree in Computer Science, Computer Engineering, Electrical Engineering, related STEM field or equivalent experience.

  • 5+ years of relevant work experience

  • Strong proficiency in modern C++ (design, implementation, debugging, and performanceconsiderations).

  • Experience designing, maintaining, and refactoring software libraries and APIs with long-termsupport in mind.

  • Comfort working in large, multi-repository or multi-component codebases with layereddependencies.

  • Demonstrated ability to lead or drive triage of difficult reliability issues and produce clear root-causeanalysis.

  • Ability to clearly communicate software architecture and design tradeoffs, including using diagramsand written design docs.

  • Low-level platform software experience (e.g., firmware/boot flows, RTOS, BMCs/MCUs, RISC-V, orclosely related system software).

  • Linux systems experience that includes driver or kernel-adjacent interfaces (e.g., VFIO or similarsubsystems).

  • Hardware bring-up and/or system triage experience (fault analysis, system diagnostics, or validationsupport in lab environments).

Ways to stand out from the crowd:

  • Distributed systems experience (e.g., MPI, gRPC, RPC frameworks, coordination/telemetry patterns).

  • Experience with inference systems and token serving (e.g., vLLM or similar serving/runtime stacks).

  • Experience shipping and supporting customer-facing SDKs, including documentation and ABIcompatibility practices.

  • Production readiness and delivery experience (e.g., CI/CD and release workflows, monitoring/alerting practices, Kubernetes and/or data center operational workflows).

The GPU started out as the engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs deep learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Today, NVIDIA GPUs are used broadly for deep learning, and NVIDIA is increasingly known as "the AI computing company."

Widely considered to be one of the technology world's most desirable employers, NVIDIA has some of the most forward-thinking and hardworking people in the world inventing the future with us. Are you a creative and collaborative software engineer seeking new challenges? If so, we want to hear from you! Come, join us and help build the real-time, cost-effective AI computing platform driving our success in this exciting and quickly growing field.

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 for Level 3, and 170,000 CAD - 220,000 CAD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until March 22, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.


Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993