Machine Learning Engineer/Scientist

Machine Learning Engineer/Scientist

St. Jacobs, ON, Canada


At Huron, we're applying machine learning techniques to develop solutions in pathology that are modernizing healthcare, helping pathologists detect cancer and other diseases. We're planning to apply our products in clinical pathology and drug development. The team at Huron is working with unique Artificial Intelligence (AI)/Machine Learning (ML) technologies that are focused on advancing medicine and improving patient care.
We're looking for experienced machine learning engineer/scientist to join our team and help advance our understanding and solve challenges in computational pathology.

Company Description

Based in St. Jacobs, Ontario, Canada, Huron Digital Pathology has a 20+ year history designing sophisticated imaging instrumentation. Our end-to-end digital whole slide imaging solutions combine the award winning TissueScope™ digital slide scanner, image management software, and workflow enhancing accessories. We believe that innovation is the key to making digital pathology a ubiquitous reality. But for us, innovation is about more than just delivering great image quality and fast scanning speeds. It’s also about designing products that are simple to use, easy to integrate with your workflow, and have attractive price-performance characteristics.

Key Responsibilities

  1. Designing AI/ML pipelines for histopathology images
  2. Research and implement appropriate ML algorithms and tools using deep learning and artificial neural networks
  3. Develop machine learning applications according to requirements
  4. Select appropriate datasets and data representation methods
  5. Analyze results for robustness, validity, and out of sample stability
  6. Run machine learning tests and experiments
  7. Perform statistical analysis and fine-tuning using test results
  8. Train and retrain systems, classifiers and networks when necessary
  9. Extend existing ML libraries and frameworks
  10. Keep abreast of developments in the field
  11. Document, summarize, and present findings to a group of peers and stakeholders.

Qualifications & Experience

  1. MSc/PhD in Engineering, Computer Science, Mathematics or similar field, preferably PhD.
  2. 2+ years full time employment or postdoctoral experience building and validating predictive models on structured and unstructured data
  3. Experience with supervised and unsupervised machine learning algorithms, and ensemble methods, such as regression, deep neural networks, decision trees, gradient boosting, linear and non-linear models
  4. Strong knowledge of neural networks, data augmentation, clustering, and deep learning
  5. Understanding of data structures, data modeling and software architecture
  6. Deep knowledge of math, probability, statistics and algorithms
  7. Ability to write code in Python, Java, and C++
  8. Familiarity with machine learning frameworks (Keras/PyTorch/Tensorflow )
  9. Excellent communication skills
  10. Ability to work in a team
  11. Outstanding analytical and problem-solving skills

Additional Desired Skills