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Machine Learning Phd Research Jobs in Toronto, ON

Career Renew

Senior Machine Learning Engineer

Toronto, ON · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... research velocity and prototype new approaches Required Qualifications PhD (preferred) or Master ...

Career Renew

Senior Machine Learning Engineer

Toronto, ON · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... research velocity and prototype new approaches Required Qualifications PhD (preferred) or Master ...

Waabi

Research Engineer

Toronto, ON · On-site +1

CA$122K - CA$215K/yr

To learn more visit: www.waabi.ai As a Research Engineer, you will be at the forefront of advancing ... Master/PhD in machine learning, computer science, engineering, or a related field. * Experience in ...

Invision AI

Machine Learning Engineer

Toronto, ON · Hybrid

We are looking for a Machine Learning Engineer to join our Toronto team and help us take our ... While the work may involve researching and implementing new approaches, this is primarily an ...

Invision AI

Machine Learning Engineer

Toronto, ON · On-site

We are looking for a Machine Learning Engineer to join our Toronto team and help us take our ... While the work may involve researching and implementing new approaches, this is primarily an ...

Td

Machine Learning Engineer II

Toronto, ON

CA$154K - CA$199K/yr

Our research broadly spans the field of machine learning with areas such as deep learning and generative AI, time series forecasting and responsible use of AI. We have access to massive financial ...

Waabi

Research Scientist

Toronto, ON · On-site

CA$158K - CA$269K/yr

As a research scientist, you will invent new AI technologies that enable our launch of fully ... Masters/PhD degree in Computer Science, AI, Machine Learning, Computer Vision, Robotics and/or ...

Td

Senior Machine Learning Engineer

Toronto, ON

CA$170K - CA$250K/yr

We are driven to be at the cutting edge of machine learning in research, engineering, and impactful applications. We are looking for world-class engineers to tackle cutting-edge problems in Machine ...

Waabi

Research Scientist, Learnable Planner

Toronto, ON · On-site +1

CA$158K - CA$269K/yr

MS/PhD degree in Computer Science, AI, Machine Learning, Computer Vision, Robotics and/or similar technical field(s) of study. Exceptional Bachelor's students will also be considered. * Experience in ...

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All JobsMachine Learning Phd Research JobsMachine Learning Phd Research Jobs in Toronto, ON

Machine Learning Phd Research information

Infographic showing various Machine Learning Phd Research job openings in Toronto, ON as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution.

Senior Machine Learning Engineer

Toronto, ON • Remote

Career Renew
See more jobs at Career Renewexternal

$165K - $225K/yr

Full-time

Re-posted 19 days ago

Job description

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus equity.
 
We are the leading virtual staining company revolutionizing digital pathology adoption worldwide through cutting-edge AI-powered technology. Our solutions deliver diagnostic-quality results in minutes while preserving tissue samples for comprehensive analysis.
Our breakthrough DeepStain™ and ReStain™ technologies enable unlimited virtual staining from a single tissue sample, eliminating the bottlenecks and limitations of traditional chemical staining processes. This innovation supports the critical evolution from research applications to clinical deployment, empowering laboratories to advance their digital pathology capabilities while reducing chemical waste, improving operational efficiency, and expanding diagnostic possibilities.

About the Role

We are seeking an experienced Senior ML Engineer to join our team who owns the representation-learning and generative modeling stack that powers Pictor’s virtual staining. The ideal candidate will have deep expertise in Machine Learning and building generalizable, production-ready models, and evaluations that stand up in clinical workflows.
      Design and implement novel computer vision and deep learning algorithms for virtual staining and digital pathology applications
      Conduct rigorous experiments to evaluate algorithm performance, validate research hypotheses, and drive iterative improvements
      Develop and advance ML models leveraging Vision Transformers, Diffusion Models, GANs, and generative architectures for image-to-image translation tasks
      Apply classical and learned image enhancement, denoising, and semantic segmentation techniques to histopathology imaging challenges
      Explore image representation in latent space for efficient, high-fidelity virtual staining
      Stay current with state-of-the-art research, identifying opportunities to apply novel techniques to PictorLabs’ product roadmap

Collaboration
      Collaborate with ML Engineering and software teams to translate research prototypes into production-ready systems meeting latency and throughput requirements
      Work with large-scale pathology datasets to train, validate, and fine-tune foundation models and custom architectures
      Partner with software engineers, data scientists, and pathology domain experts to integrate research into production systems
      Contribute to best practices for data engineering, data governance, and data quality across research and production pipelines
      Leverage AI coding and ideation tools to accelerate research velocity and prototype new approaches

Required Qualifications

      PhD (preferred) or Master’s degree in Computer Science, Electrical Engineering, or a related field
      Deep expertise in computer vision and deep learning, with hands-on experience in one or more of: Vision Transformers, Diffusion Models, GANs, semantic segmentation, or classical image enhancement and denoising
      Expert proficiency in Python and PyTorch and other scientific computing environments a plus
      Strong mathematical foundation in linear algebra, probability, and optimization
      Experience with large-scale model training, distributed computing, or cloud ML infrastructure (AWS, GCP, or Azure)
      Knowledge of handling large scale image data,  data version controls,  model registry, has experience dealing with ML lifecycles
      Experience with feature search, data balancing, and data curation pipelines.
      Knowledge of software engineering best practices including version control (Git) and CI/CD pipelines
      Excellent collaboration and communication skills, with the ability to work effectively in a fast-paced, cross-functional international startup environment
      Extensive use of AI tools for coding, optimization, and ideation

Preferred Qualifications

      Experience with medical imaging, digital pathology, or whole slide image (WSI) processing
      Experience with LoRAs,  transformer architecture and state of the art image to image translation models (Flux 2, Z-Image) and the Hugging face ecosystem
      Background in generative models and fine-tuning of foundation models
      Experience with GPU acceleration and optimization, including CUDA kernel engineering, TensorRT/ONNX export, and inference serving frameworks such as Triton
      Experience with hosting  computer vision model inference on NVIDIA DGX Spark.
      Understanding of FDA regulatory requirements for AI/ML in medical devices
      Experience with MLOps tools (MLflow, Kubeflow) and model versioning practices
      Develop tools and frameworks to streamline ML research workflows, experimentation, and reproducibility

What We Offer

The opportunity to work on technology that directly improves patient outcomes and transforms clinical diagnostics, alongside a talented team of engineers and researchers pushing the boundaries of AI in healthcare. You will have the freedom to pursue high-impact research while seeing your work deployed at scale in real clinical environments.