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Pytorch Developer Jobs in Ontario (NOW HIRING)

Proficiency in Python and familiarity with ML libraries like scikit-learn, PyTorch, or TensorFlow ... Growth path toward senior AI engineering or solution architecture roles * An innovative and ...

You will collaborate with engineers and stakeholders and drive innovation by applying GenAI to ... TensorFlow, PyTorch LLMs: Llama, Gemini, GPT-4, and other advanced LLMs. Vector Databases: Pinecone ...

You will collaborate with research and product engineering from various domains including design ... Exposure to popular machine learning frameworks ( TensorFlow , PyTorch ) and their integration into ...

... 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 ...

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

Strong programming skills in Python and experience with libraries such as PyTorch, TensorFlow, scikit-learn, NumPy, and Pandas. * Experience working with large datasets, SQL, and data processing ...

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

Design scalable and resilient ML systems using frameworks such as PyTorch and TensorFlow ... Strong programming skills in Python; experience with LangChain, LangGraph, or related frameworks is ...

Senior Machine Learning Engineer

Toronto, ON · 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 ...

Senior Machine Learning Engineer

Ottawa, ON · 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 ...

Senior Machine Learning Engineer

Oakville, ON · 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 ...

Senior Machine Learning Engineer

London, ON · 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 ...

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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 Ontario?

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

Infographic showing various Pytorch Developer job openings in Ontario as of August 2026, with employment types broken down into 75% Full Time, 12% Part Time, and 13% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution.

Senior Privacy-Enhancing Technologies (PETs) Developer

Alquemy

Ottawa, ON • On-site

Full-time

Posted 6 days ago


Job description

Job Description Senior Privacy-Enhancing Technologies (PETs) Developer Role Summary We are seeking a Senior Developer with expertise in Privacy-Enhancing Technologies (PETs) to develop scalable, production-ready privacy solutions across complex data environments. The role requires strong experience in Python, data engineering, cloud infrastructure, and DevOps. Key Responsibilities Develop and implement PET solutions for structured and unstructured data.

Integrate open-source libraries and platforms into production environments. Build and test proof-of-concept solutions for performance, scalability, and privacy. Develop and optimize ETL/data pipelines for data processing and sanitization.

Provision and manage cloud infrastructure and DevOps workflows. Evaluate emerging technologies and provide technical recommendations. Create technical documentation, reports, and project deliverables.

Key Qualifications Active Secret-level security clearance or eligibility to obtain one. Master's or Ph.D. in Computer Science, Data Science, AI/ML, Cybersecurity, Cryptography, Mathematics, Statistics, or related field

5+ years of Python development with tools such as pandas, NumPy, SciPy, PySpark, PyTorch, scikit-learn, or Polars. 3+ years of DevOps experience, including CI/CD, version control, and software engineering best practices. Hands-on experience with PETs such as anonymization, differential privacy, synthetic data, federated learning, homomorphic encryption, or SMPC.

Experience with Azure, Fabric, Azure Data Lake, Databricks, Docker, Terraform/Ansible, and Linux. Knowledge of advanced ML techniques including Transformers, GANs, Autoencoders, and RAG. Experience working with large and complex datasets, preferably in regulated environments.