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Image Processing Medical jobs in Toronto, ON

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    • Expertise in medical imaging analysis or signal processing with AI.
    • Remain aware of new innovations in the use of AI/ML in medical imaging and ultrasound.
    • View all Oncoustics jobs - Toronto jobs - Machine Learning Engineer jobs in Toronto, ON
    • Salary Search: Senior Machine Learning Engineer in Medical Imaging salaries in Toronto, ON
    • Be comfortable discussing technical concepts (e.g. DICOM image handling, cloud architecture, networking/security) to make informed decisions together with the…
    • Assist in study visits (e.g. assessment, adverse events, monitoring safety, medication, questionnaires, sample collection, including processing and shipment of…
    • Ability to undertake high quality image post processing.
    • An MSc in image processing development and application supporting the large volume required for image…
    • The Chair will have demonstrated an ability to work collaboratively across disciplines and medical specialties and will develop the field of AI through research…
  • View similar jobs with this employer
    • Other tasks will include processing/statistical analysis of medical images (particularly fMRI preprocessing and analysis), optimizing computational pipelines,…
    • Experience in medical image analysis.
    • Deep learning for medical image analysis.
    • Develop and validate deep learning algorithms for medical image segmentation,…
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Job Post Details

Senior Machine Learning Engineer in Medical Imaging - job post

Oncoustics
Toronto, ON
Full-time
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Job details

Job type

  • Full-time

Location

Toronto, ON

Full job description

TORONTO: RESEARCH AND DEVELOPMENT - FULL TIME
Job Description
Oncoustics is revolutionizing the use of point of care ultrasound in liver care through advanced AI. We are supported by high-profile institutional investors and have deep partnerships in place with several major ultrasound and pharmaceutical players. We are looking to hire a senior ML Engineer to join our team with relevant academic experience and deep industry experience. ‍

A successful candidate will be capable of in-depth development and understanding of machine learning architectures that go beyond the state of the art—advancing beyond conventional hyper-parameter tuning on existing models. They should be able to manage and lead both teams and projects, while effectively coordinating with signal processing, clinical data, and product teams. The ideal candidate will have strong expertise in processes, pipelines, operations, QA, and writing production-grade code. They should be able to build on previous work to drive innovation with a novel dataset and demonstrate a collaborative, team-oriented mindset.
Responsibility
  • Lead development and deployment of deep learning and machine learning models in tensorflow and pytorch
  • Build on existing collaborative culture in multi-disciplinary & distributed team
  • Coach on and explain ML engineering (options, cost-benefit, etc) to ML scientists and team overall
  • Help the ML and software teams understand the necessary parts of ML to properly develop supporting systems and processes
  • Coach both ML scientists and ML/software engineers on appropriate best ML software practices
  • Work w/ R&D team to improve experiment foci (IE prioritization and targeted results) and communications (presentations, updates, etc)
  • Define and manage ML engineering processes and pipelines between R&D and SW engineering for final product outputs.
  • Design models/learning strategies to optimize mining of unique ultrasound signal data with deep learning
  • Adopt state of the art algorithms and models for that include multi-instance learning strategies, attention and GANs
  • Plan for deployment of all models in Oncoustics future apps
  • Remain aware of new innovations in the use of AI/ML in medical imaging and ultrasound
  • Participate in FDA planning and clearance of algorithms
Requirements
  • Graduate degree in a related field, and relevant undergraduate
  • 5+ years at least of industry experience in the development and deployment of AI/ML models for health care
  • Expertise in Python for Deep Learning and Machine Learning packages: Pandas, Sklearn, Keras, Tensorflow, Pytorch
  • Deep Learning architecture design: Experience with attention mechanisms, multi-instance learning and/or GANs
Good To Have
  • PhD/graduate work in machine learning/machine vision
  • Expertise in medical imaging analysis or signal processing with AI
  • Experience in the use of ultrasound
  • Prior experience with FDA clearance of AI/ML algorithms
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