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Pytorch Developer Jobs in British Columbia (NOW HIRING)

Targeted Talent

Senior Deep Learning Engineer

Vancouver, BC · 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 ... Proficiency in deep learning frameworks like Tensorflow and/or PyTorch * Experience with CNNs ...

Targeted Talent

Senior Deep Learning Engineer

Vancouver, BC · 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 ... Proficiency in deep learning frameworks like Tensorflow and/or PyTorch * Experience with CNNs ...

Fortinet, Inc.

AI Application Developer

Burnaby, BC · On-site

CA$107K - CA$179K/yr

... or PyTorch. * LLM Application Development: Proven experience building applications with Large ... RAG). * DevOps Knowledge: Hands-on experience with CI/CD tools, containerization (Docker ...

Fortinet

AI Application Developer

Burnaby, BC

CA$107K - CA$179K/yr

... or PyTorch. * LLM Application Development: Proven experience building applications with Large ... RAG). * DevOps Knowledge: Hands-on experience with CI/CD tools, containerization (Docker ...

BDO Canada

Senior Machine Learning Engineer

Vancouver, BC · On-site

CA$84K - CA$128K/yr

Implement CI/CD workflows using tools such as Azure DevOps or GitHub Actions. * Ensure operational ... Strong knowledge of LLM frameworks and libraries (such as transformers, trl, deepspeed, PyTorch ...

KPMG

Manager, ML/AI Engineer, Data & AI

Vancouver, BC · On-site

Execute ML/AI engineering tasks including exploratory data analysis, data preparation, model ... TensorFlow, PyTorch, Azure ML Studio, Databricks MLFlow). * Develop and optimize AI and GenAI ...

Dialpad

AI Engineer, Voice Designer

Vancouver, BC · On-site

PyTorch). * Speech Expertise: 3+ years of experience in Speech Synthesis (TTS) or Voice Design ... Prompt Engineering: Proven experience crafting and evaluating LLM prompts (system, few-shot) and ...

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Pytorch Developer information

What is a PyTorch Developer?

A PyTorch Developer is a software engineer or data scientist who specializes in using PyTorch, an open-source machine learning library, to build and deploy deep learning models. Their responsibilities typically include designing neural network architectures, training and evaluating models, and optimizing code for performance. PyTorch Developers work in fields such as artificial intelligence, computer vision, and natural language processing, collaborating with teams to solve complex problems using machine learning. They are proficient in Python and have a strong understanding of deep learning concepts. Additionally, they often contribute to research, development, and the deployment of AI solutions in production environments.

What are the key skills and qualifications needed to thrive as a Pytorch Developer, and why are they important?

To thrive as a Pytorch Developer, you need strong programming skills in Python, a solid grasp of machine learning concepts, and experience with deep learning frameworks—especially PyTorch itself. Familiarity with tools like CUDA, Jupyter Notebooks, and version control systems (e.g., Git) is typically expected, along with knowledge of cloud platforms or relevant certifications. Problem-solving ability, effective collaboration, and clear communication are crucial soft skills for success in this role. These skills and qualities are vital for efficiently building, optimizing, and deploying machine learning models in real-world applications.

What is the difference between Pytorch Developer vs Machine Learning Engineer?

AspectPytorch DeveloperMachine Learning Engineer
Required CredentialsBachelor's or higher in CS, experience with PyTorchBachelor's or higher in CS, data science, or related field, with ML experience
Work EnvironmentResearch labs, AI startups, tech companies focusing on deep learningTech companies, finance, healthcare, often involving deployment and scaling ML models
Industry UsagePrimarily in AI research and development teamsAcross industries implementing ML solutions in production

While both roles require knowledge of machine learning and experience with PyTorch, a Pytorch Developer mainly focuses on developing and optimizing deep learning models using PyTorch. A Machine Learning Engineer often has a broader scope, including deploying, maintaining, and scaling ML models across various platforms and industries.

What are some common challenges Pytorch Developers face when deploying machine learning models to production environments?

Pytorch Developers often encounter challenges when transitioning models from research to production, such as optimizing model performance for inference speed and memory usage, ensuring compatibility with deployment frameworks like TorchScript or ONNX, and managing dependencies across different systems. Additionally, integrating PyTorch models into existing software stacks and maintaining reproducibility can be complex. Collaborating closely with DevOps and data engineering teams is crucial to address these issues and ensure smooth deployment.
What are popular job titles related to Pytorch Developer jobs in British Columbia? For Pytorch Developer jobs in British Columbia, the most frequently searched job titles are:
What job categories do people searching Pytorch Developer jobs in British Columbia look for? The top searched job categories for Pytorch Developer jobs in British Columbia are:
Pytorch Developer jobs near you
Infographic showing various Pytorch Developer job openings in British Columbia as of July 2026, with employment types broken down into 85% Full Time, 3% Part Time, 1% Temporary, and 11% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution.
Compiler Engineer - MLIR / PyTorch Infrastructure

Compiler Engineer - MLIR / PyTorch Infrastructure

Mythic

Vancouver, BC

Full-time

Posted 14 days ago

Job description

About us
Mythic is building the future of AI computing with breakthrough analog technology that delivers 100 the performance of traditional digital systems at the same power and cost. This unlocks bigger, more capable models and faster, more responsive applications-whether in edge devices like drones, robotics, and sensors, or in cloud and data center environments. Our technology powers everything from large language models and CNNs to advanced signal processing, and is engineered to operate from -40 C to +125 C, making it ideal for industrial, automotive, aerospace, and defense.

We've raised over $100M from world-class investors including Softbank, Threshold Ventures, Lux Capital, and DCVC, and secured multi-million-dollar customer contracts across multiple markets.

About the role
Join us in advancing the MLIR ecosystem at Mythic. You'll help extend our existing high-level dialects and design a new hardware-aware low-level dialect, building conversion paths that bridge to our current IRs. Working closely with hardware engineers and ML developers, your work will expand interoperability with PyTorch and other frameworks, laying the groundwork for long-term innovation. The result: an MLIR-based stack that unifies hardware constraints with developer needs and accelerates adoption of modern ecosystems.
Here's what you will do
  • Architect the migration of the existing compiler flow into MLIR, defining dialects, passes, and lowering strategies.
  • Build conversion paths between MLIR and Mythic's custom low-level IR to keep both flows operational during migration.
  • Define validation infrastructure within MLIR, including interpretation or execution paths for simulation and debugging.
  • Enable compilation by extending MLIR integration across analog accelerators and digital subsystems.
  • Leverage Torch-MLIR where PyTorch inputs are available, and guide future integration with PyTorch 2.0 compiler technologies (TorchInductor, TorchDynamo, Torch-MLIR)
Here's the background we hope you will have
  • 3+ years of experience in compiler or high-performance systems development.
  • Proficiency in modern C++ (C++14/17/20) and Python.
  • Direct, hands-on experience with MLIR, including dialect design, compiler passes, or lowering pipelines.
  • Strong understanding of compiler IRs and transformations, with the ability to reason about lowering from high-level ops to hardware-aware representations.
The following would be nice to have, but is not required
  • Experience architecting complete MLIR flows: from frontend dialects down to hardware-aware dialects, including conversion to and from existing IRs.
  • Familiarity with PyTorch compiler technologies, especially Torch-MLIR and integration paths with PyTorch 2.0 (TorchDynamo, TorchInductor).
  • Knowledge of dataflow architectures, scheduling, and memory orchestration.
  • Background in heterogeneous or specialized accelerators (e.g., analog compute, NPUs, GPUs, DSPs).
What we offer
  • Shape the MLIR and PyTorch integration strategy for novel AI hardware.
  • Opportunity to contribute upstream and influence the broader ML compiler ecosystem.
  • Collaborate with a team spanning hardware, runtime, and compiler design.
  • Competitive compensation, equity, and comprehensive benefits.
At Mythic, we foster a collaborative and respectful environment where people can do their best work. We hire smart, capable individuals, provide the tools and support they need, and trust them to deliver. Our team brings a wide range of experiences and perspectives, which we see as a strength in solving hard problems together. We value professionalism, creativity, and integrity, and strive to make Mythic a place where every employee feels they belong and can contribute meaningfully.
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