Deep Learning Engineer – Computational Pathology

2 weeks ago

Toronto ON MG X, Canada University of Toronto Full time $90,000 - $120,000 per year

Job Summary

The University Health Network (UHN) is seeking a highly motivated Deep Learning Engineer to join our Computational Pathology and Biomarker Discovery research program. The successful candidate will focus on deploying and optimizing deep learning algorithms for quantitative biomarker assessment from cloud-hosted whole-slide histopathology images.

You will collaborate closely with pathologists, biomedical researchers, and AI scientists to design, implement, and deploy scalable deep learning pipelines that enable high-throughput, reproducible biomarker quantification. This role is central to advancing precision oncology and translational research efforts at UHN.

Duties

  • Develop, optimize, and deploy deep learning models for digital pathology image analysis (e.g., cell segmentation, tissue classification, biomarker scoring).
  • Design and implement scalable, cloud-based workflows for processing large whole-slide image datasets.
  • Optimize model inference and performance using GPU computing, containerization, and workflow automation tools.
  • Evaluate and validate model performance using appropriate metrics, statistical methods, and explainable AI techniques.
  • Ensure code quality through documentation, version control, and adherence to reproducible research practices.
  • Support integration of developed models and pipelines into existing research and clinical infrastructures.

Requirements

  • Master's degree in Computer Science, Biomedical Engineering, Electrical Engineering, or a closely related field.
  • Strong background in deep learning and computer vision (e.g., CNNs, segmentation networks, transformer-based models).
  • Proven experience in deploying and optimizing deep learning algorithms for production or research environments, particularly with GPU-based or cloud infrastructure.
  • Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
  • Hands-on experience with model inference optimization, containerization (Docker), and workflow automation for scalable deployment.
  • Experience with medical or microscopy image analysis preferred (e.g., histopathology, radiology).
  • Familiarity with image processing libraries (OpenCV, scikit-image), data handling tools (NumPy, pandas), and version control systems (Git).
  • Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and integrating AI models into cloud-based data pipelines.
  • Excellent communication skills and a demonstrated ability to collaborate in an interdisciplinary research environment.

Job Type: Full-time

Pay: From $75,000.00 per year

Work Location: Hybrid remote in Toronto, ON M5G 1X7

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