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Cuda Engineer Jobs in Ontario (NOW HIRING)

Clockwork.io

CA$150K - CA$230K/yr

Work with internals of frameworks like PyTorch, NCCL, CUDA runtime-not as a user, but modifying and ... GPU programming (CUDA) or GPU systems experience * High-performance networking (RDMA, InfiniBand)

Targeted Talent

Senior Deep Learning Engineer

Toronto, ON · On-site +1

$130K - $180K/yr

We're seeking top-notch engineers to join our team. As part of our group, you'll collaborate with ... Knowledge of CUDA/OpenGL * Experience deploying neural networks in production * Familiarity with ...

Targeted Talent

Senior Deep Learning Engineer

Toronto, ON · On-site +1

$130K - $180K/yr

We're seeking top-notch engineers to join our team. As part of our group, you'll collaborate with ... Knowledge of CUDA/OpenGL * Experience deploying neural networks in production * Familiarity with ...

Teledyne

Senior Software Developer

Concord, ON · On-site

CA$93K - CA$124K/yr

GPU/CUDA programming knowledge * Advantage: Experience with lidar or geospatial systems * Advantage: Background in mathematical modelling or algorithms * Required: Degree in Computer Science or ...

Boson AI

Site Reliability Engineer

Toronto, ON · On-site +1

CA$125K - CA$250K/yr

We are looking for a Site Reliability Engineer to help build and operate the infrastructure behind ... GPU and server administration, including CUDA drivers, firmware, BIOS, and hardware troubleshooting

Actalent

DSP Algorithm Engineer

Ottawa, ON

CA$60 - CA$80/hr

DSP Algorithm Engineer Join a central AI and chip engineering organization at a leading technology ... Knowledge of DSP frameworks and parallel computing technologies such as OpenCL, CUDA, or OpenGL.

New

Quincus

Machine Learning Engineer

Toronto, ON

... programming using CUDA, OpenCL, or similar libraries. - Experience with distributed systems and cloud computing platforms such as Kubernetes, Docker, GCP, and AWS. Preferred Qualifications: - Ph.D ...

Arcadion

HPC Specialist

Ottawa, ON · On-site

... research, engineering simulations, AI/ML workloads, and large-scale data analytics. Core ... Benchmark workloads and tune for performance (e.g., MPI, CUDA, OpenMP) * Optimize I/O and inter ...

Roche

Software Engineer

Mississauga, ON · On-site

The Position Software Engineer A healthier future. It's what drives us to innovate. To continuously ... Experience with CUDA or GPU-accelerated libraries (CuPy, RAPIDS). Relocation benefits are not ...

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Cuda Engineer information

What is a CUDA engineer?

CUDA Engineers are software developers who specialize in using NVIDIA's CUDA (Compute Unified Device Architecture) platform to write programs that run on Graphics Processing Units (GPUs). They optimize and accelerate computational tasks by parallelizing code, making use of GPUs’ capabilities for high-performance computing. CUDA Engineers often work in fields like machine learning, scientific computing, and graphics, where large amounts of data need to be processed quickly. Their expertise includes proficiency in C/C++, CUDA programming, and understanding GPU hardware and parallel computing concepts.

What are the key skills and qualifications needed to thrive as a CUDA engineer?

To thrive as a CUDA Engineer, you need a strong proficiency in C/C++ programming, parallel computing concepts, and deep knowledge of GPU architectures, often supported by a computer science or engineering degree. Experience with NVIDIA CUDA Toolkit, profiling/debugging tools, and sometimes certifications like NVIDIA DLI are highly valuable. Strong problem-solving, attention to detail, and effective communication skills help you optimize code and collaborate across teams. These skills ensure efficient development of high-performance GPU applications and successful project delivery in compute-intensive fields.

What are some common challenges faced by CUDA engineers when optimizing GPU-accelerated applications?

CUDA Engineers frequently encounter challenges such as managing memory effectively between the host and the device, optimizing kernel performance, and minimizing data transfer bottlenecks. Debugging parallel code can also be complex due to race conditions and the difficulty of reproducing timing-related bugs. Collaborating closely with software developers and data scientists is essential to ensure that GPU resources are leveraged efficiently and that the application's overall performance meets project goals.

What is the difference between Cuda Engineer vs GPU Developer?

AspectCuda EngineerGPU Developer
Required CredentialsBachelor's or Master's in Computer Science, Engineering, or related; knowledge of CUDA, C++, parallel programmingBachelor's or Master's in Computer Science, Engineering, or related; experience with GPU programming, CUDA, OpenCL
Work EnvironmentResearch labs, tech companies, hardware firms focusing on GPU accelerationSoftware development teams, gaming, AI, scientific computing sectors
Employer & Industry UsageHardware manufacturers, AI companies, high-performance computing firmsGame development, scientific research, machine learning applications

While both roles involve GPU programming and CUDA expertise, a Cuda Engineer primarily focuses on developing and optimizing CUDA-based solutions for hardware acceleration. In contrast, a GPU Developer works on broader GPU programming tasks, including application development across various platforms. The roles often overlap but differ in scope and specific focus areas.

What are popular job titles related to Cuda Engineer jobs in Ontario?

For Cuda Engineer jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Cuda Engineer jobs in Ontario look for?

The top searched job categories for Cuda Engineer jobs in Ontario are:

What cities in Ontario are hiring for Cuda Engineer jobs?

Cities in Ontario with the most Cuda Engineer job openings:

Cuda Engineer jobs near you
Infographic showing various Cuda Engineer job openings in Ontario as of August 2026, with employment types broken down into 85% Full Time, 12% Part Time, and 3% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution.

Senior Software Developer - Numerical

Seequent

Toronto, ON • On-site

Full-time

Re-posted 13 days ago

Job description

The Role

Reporting to the Director, Software Development (or delegate), we are seeking an experienced Senior Software Developer - Numerical to join our geoscience software development team. This role is based in Toronto, ON, operating under a hybrid work model.

This position focuses on transforming early-stage research prototypes into high-quality, production-ready numerical software. You will design, implement, and optimize high-performance numerical libraries and compute kernels using C++, Python, and CUDA, ensuring scalability, robustness, and performance.

Working closely with researchers and domain experts, this role bridges scientific research and software engineering, requiring strong numerical expertise, performance-focused thinking, and effective cross-functional collaboration.

In this role, you will have the opportunity to

Numerical Software Development

  • Develop and optimize high-performance numerical software in C++, Python, and CUDA.
  • Re-engineer research prototypes into scalable, production-ready solutions.
  • Implement parallel programming techniques including multi-threading, vectorization, and GPU acceleration.
  • Ensure solutions are portable across Linux (primary) and Windows environments.

Performance & Quality

  • Profile, benchmark, and optimize numerical workflows using tools such as Nsight and VTune.
  • Improve runtime efficiency, memory usage, and algorithmic scalability.
  • Design automated testing and verification frameworks to ensure numerical correctness and reliability.

Collaboration & Engineering Excellence

  • Work closely with researchers, engineers, and product teams to translate research concepts into stable implementations.
  • Participate in design reviews, technical planning, and peer code reviews.
  • Produce clear technical documentation and apply modern engineering practices, including CI/CD (GitHub Actions) and version control.

Essential Knowledge, Skills, and Experience

  • Bachelor's degree in Computer Science, Applied Mathematics, Physics, or a related STEM field.
  • 7+ years of experience in software development or engineering roles.
  • Strong experience in numerical computing with C++ and Python.
  • Hands-on experience with CUDA, GPU programming, and parallel computing.
  • Knowledge of numerical libraries such as Eigen or BLAS.
  • Experience developing on Linux and supporting cross-platform environments.
  • Familiarity with performance profiling tools and CI/CD pipelines.

Assets

  • Experience with OpenMP, Rust, Fortran, cloud computing (GCP), containerization, or distributed systems.

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