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Pytorch Developer Jobs in Montreal, QC (NOW HIRING)

LawZero

Senior ML Research Developer

Montreal, QC · On-site

We are seeking a senior machine learning (ML) research developer to join our team working on a ... PyTorch, TensorFlow, or JAX. * Ability to collaborate effectively with cross-functional teams ...

Apertera

Generative AI Engineer

Montreal, QC · On-site

... or PyTorch and optimizing performance on diverse hardware platforms. * Train and evaluate ... Work closely with software and DevOps engineers to deploy GenAI models. * Document code, algorithms ...

Tecsys Inc.

Senior Developer (AI / ML)

Montreal, QC · On-site +1

Python, NumPy, Pandas, Scikit-learn, PyTorch * LLMs, RAG, prompt engineering, and agentic AI * FastAPI (or similar) * Vector databases (PostgreSQL/pgvector preferred) * MLOps, model monitoring, 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 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 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 popular job titles related to Pytorch Developer jobs in Montreal, QC?

For Pytorch Developer jobs in Montreal, QC, the most frequently searched job titles are:

What job categories do people searching Pytorch Developer jobs in Montreal, QC look for?

The top searched job categories for Pytorch Developer jobs in Montreal, QC are:

Pytorch Developer jobs near you

Senior Machine Learning Engineer

Jumio

Montreal, QC

Full-time

Re-posted yesterday

Job description

We're looking for a Senior Machine Learning Engineer with strong computer vision expertise to join our Biometrics team. You'll ramp up on the biometrics domain while contributing to the design, training, and scaling of our ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process.

What You'll Do
  • Design and develop computer vision models and pipelines, contributing to biometrics use cases such as face detection, quality assessment, and recognition
  • Collaborate on benchmarking of models across datasets and operating conditions
  • Train and optimize models using PyTorch, TensorFlow, and/or JAX
  • Contribute to end-to-end ML pipelines, from data ingestion to deployment. Help design automated pipelines (Airflow) for data ingestion and cleaning.
  • Production Engineering: Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and support deployment on AWS.
  • Collaborate with and mentor ML engineers, and contribute to technical best practices across the Computer Vision team.
What We're Looking For
  • Experience: 5+ years of industry experience in Machine Learning with a focus on Computer Vision (e.g., image classification, object detection, segmentation, image quality, generative models)
  • Strong Computer Vision fundamentals
  • Fairness & Ethics: Awareness of algorithmic bias and willingness to learn domain-specific fairness practices
  • Strong Engineering: Strong proficiency in Python (Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code
  • Systems Architecture: Experience designing or contributing to ML pipelines and familiarity with orchestration tools like Airflow
  • Cloud Native: Experience with GPU-based training and deploying ML services on AWS
Nice to Have
  • Research Publications in top computer vision venues (CVPR, ICCV, ECCV)
  • Large Scale Search: Familiarity with vector databases and ANN search
  • Synthetic Data: Experience with GANs or diffusion models for data augmentation
  • Mobile/Edge Experience: CoreML, LiteRT, and/or TFLite
  • Familiarity with privacy, security, and compliance considerations in sensitive ML applications

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