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Parallel Programming Jobs in Toronto, ON (NOW HIRING)

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Lead AI Engineer

Toronto, ON · On-site +1

Title and Summary Lead AI Engineer Overview We are looking for a talented Lead AI Engineer to work ... Strong foundational experience with PySpark and a solid understanding of distributed and parallel ...

TripArc

Delivery Manager

Toronto, ON

This Delivery Manager role exists to keep that parallel delivery coherent: ceremonies running tight ... Candidates who have led delivery for AI-assisted engineering teams and built operational frameworks ...

Range

Delivery Manager

Toronto, ON

This Delivery Manager role exists to keep that parallel delivery coherent: ceremonies running tight ... Candidates who have led delivery for AI-assisted engineering teams and built operational frameworks ...

Career Renew

Research Crawling Engineer

Toronto, ON · Remote

$80K - $175K/yr

Strong programming experience in one or more of: Go, Rust, Python, Java, or C++ * Experience ... Familiarity with distributed systems and parallel processing * Experience working with large ...

Waabi

Research Engineer, Calibration

Toronto, ON · On-site +1

CA$158K - CA$269K/yr

... parallel, and distributed computing techniques for efficient computation. - Publications in top-tier conferences or journals related to high-performance computing, image processing, computer graphics ...

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Research Crawling Engineer

Toronto, ON · Remote

$80K - $175K/yr

Strong programming experience in one or more of: Go, Rust, Python, Java, or C++ * Experience ... Familiarity with distributed systems and parallel processing * Experience working with large ...

Amd

Principal AI/ML SW/HW Co-Design Lead

Thornhill, ON · On-site

The ideal candidate should be passionate about AI/ML engineering and possess leadership skills to ... Familiar with GPU/TPU/CPU SOC architectures including SIMD/SIMT/Parallel Processing models, Cache ...

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Parallel Programming information

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$22.4K

$105.1K

$143.2K

How much do parallel programming jobs pay per year?

As of May 29, 2026, the average yearly pay for parallel programming in Toronto, ON is $105,124.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,550.00 and $133,607.00 per year, depending on experience, location, and employer.

What is a Parallel Programming job?

A Parallel Programming job involves developing software that can execute multiple tasks or computations simultaneously to improve performance and efficiency. Professionals in this field work with multi-core processors, distributed systems, and GPU computing to optimize software for speed and scalability. They typically use programming models like MPI, OpenMP, or CUDA to implement parallelism. Industries such as high-performance computing, data science, and machine learning heavily rely on parallel programming to handle large-scale computations.

What are the key skills and qualifications needed to thrive in the Parallel Programming position, and why are they important?

To excel in Parallel Programming, you need a solid background in computer science, strong proficiency in languages such as C/C++, Python, or Java, and experience with parallel computing frameworks. Familiarity with tools like OpenMP, MPI, CUDA, or parallel processing libraries, as well as relevant certifications or coursework, is highly valuable. Analytical thinking, collaboration, and effective problem-solving are essential soft skills for success in this role. These competencies enable professionals to efficiently develop, debug, and optimize scalable applications in high-performance computing environments.

What are some typical challenges encountered in a Parallel Programming role?

Professionals in parallel programming often face challenges such as identifying code sections that can be effectively parallelized, managing data dependencies, and handling synchronization between parallel tasks. Debugging and optimizing performance in multi-threaded or distributed environments can also be complex, requiring patience and attention to detail. Collaboration with data scientists, hardware engineers, and other software developers is common, as projects frequently involve cross-functional teamwork. Overcoming these challenges is a rewarding part of the job, leading to faster, more efficient software solutions that can have a significant impact in fields like scientific computing, finance, and machine learning.

What job makes $10,000 a month without a degree?

In the field of parallel programming, highly skilled software developers or engineers working on complex systems can earn $10,000 or more per month, especially with expertise in high-demand areas like GPU programming, distributed systems, or specialized frameworks. These roles often require strong coding skills, experience with parallel algorithms, and proficiency in tools such as CUDA or OpenCL, but may not always require a formal degree if demonstrated through a strong portfolio or certifications.
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What job categories do people searching Parallel Programming jobs in Toronto, ON look for? The top searched job categories for Parallel Programming jobs in Toronto, ON are:
Parallel Programming jobs near you
Infographic showing various Parallel Programming job openings in Toronto, ON as of May 2026, with employment types broken down into 54% Full Time, 32% Part Time, and 14% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $105,124 per year, or $50.5 per hour.
Senior Machine Learning Applications and Compiler Engineer, LPX

Senior Machine Learning Applications and Compiler Engineer, LPX

Nvidia

Toronto, ON • Hybrid

Full-time

Posted 23 days ago

Job description

We are now looking for a Senior Machine Learning Applications and Compiler Engineer!

NVIDIA is seeking engineers to develop algorithms and optimizations for our LPX inference and compiler stack. You will work at the intersection of large-scale systems, compilers, and deep learning, crafting how neural network workloads map onto future NVIDIA platforms. This is your chance to be part of something outstandingly innovative!

What you'll be doing:

  • Build, develop, and maintain high-performance runtime and compiler components, focusing on end-to-end inference optimization.

  • Define and implement mappings of large-scale inference workloads onto NVIDIA's systems.

  • Extend and integrate with NVIDIA's SW ecosystem, contributing to libraries, tooling, and interfaces that enable seamless deployment of models across platforms.

  • Benchmark, profile, and monitor key performance and efficiency metrics to ensure the compiler generates efficient mappings of neural network graphs to our inference hardware.

  • Collaborate closely with hardware architects and design teams to feedback software observations, influence future architectures, and codesign features that unlock new performance and efficiency points.

  • Prototype and evaluate new compilation and runtime techniques, including graph transformations, scheduling strategies, and memory/layout optimizations tailored to spatial processors.

  • Publish and present technical work on novel compilation approaches for inference and related spatial accelerators at top tier ML, compiler, and computer architecture venues.

What we need to see:

  • MS or PhD in Computer Science, Electrical/Computer Engineering, or related field, or equivalent experience, with 5 years of relevant experience.

  • Strong software engineering background with proficiency in systems level programming (e.g., C/C++ and/or Rust) and solid CS fundamentals in data structures, algorithms, and concurrency.

  • Hands on experience with compiler or runtime development, including IR design, optimization passes, or code generation.

  • Experience with LLVM and/or MLIR, including building custom passes, dialects, or integrations.

  • Familiarity with deep learning frameworks such as TensorFlow and PyTorch, and experience working with portable graph formats such as ONNX.

  • Solid understanding of parallel and heterogeneous compute architectures, such as GPUs, spatial accelerators, or other domain specific processors.

  • Strong analytical and debugging skills, with experience using profiling, tracing, and benchmarking tools to drive performance improvements.

  • Excellent communication and collaboration skills, with the ability to work across hardware, systems, and software teams.

  • Ideal candidates will have direct experience with MLIR based compilers or other multilevel IR stacks, especially in the context of graph based deep learning workloads.

Ways to stand out from the crowd:

  • Prior work on spatial or dataflow architectures, including static scheduling, pipeline parallelism, or tensor parallelism at scale.

  • Contributions to opensource ML frameworks, compilers, or runtime systems, particularly in areas related to performance or scalability.

  • Demonstrated research impact, such as publications or presentations at conferences like PLDI, CGO, ASPLOS, ISCA, MICRO, MLSys, NeurIPS, or similar.

  • Experience with large-scale AI distributed inference or training systems, including performance modeling and capacity planning for multi rack deployments.

#LI-Hybrid

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 27, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

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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

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