Senior Machine Learning Developer

Thorasys; Montreal (administrative region); On-site; CAD 110,000 - 140,000; Full time

Job summary

THORASYS Thoracic Medical Systems Inc. in Montreal seeks a Senior Machine Learning Developer to design, validate, and deploy ML models for medical devices and digital health solutions.

You will collaborate with clinical, software, systems, and regulatory teams to transform clinical and device data into actionable insights and innovative diagnostic capabilities. Responsibilities include developing and optimizing models, establishing preprocessing pipelines, integrating AI into commercial

Qualifications

• Experience designing, validating, and deploying ML models for regulated medical devices.
• Strong programming in Python and ML frameworks.
• Familiarity with data pipelines, preprocessing, and feature engineering.
• Knowledge of ISO 13485, IEC 62304, and SaMD guidance is a plus.

Responsibilities

• Develop, train, evaluate, and optimize ML/AI models for medical applications.
• Analyze clinical and device data to identify trends and improve performance.
• Design data preprocessing, feature engineering, and model validation pipelines.
• Collaborate with software and systems engineers to integrate ML into products.
• Document development activities for regulatory submissions and quality systems.

Skills

Machine Learning

Data Analysis

Python

Software Development

Communication

Collaboration

Education

BSc in CS

MS/PhD in AI

Tools

TensorFlow

PyTorch

Scikit-learn

MLOps

Job description

THORASYS Thoracic Medical Systems Inc. is a young medical device company based in Montreal’s MileEx neighbourhood.We develop, manufacture and market advanced diagnostic medical devices incorporating novel approaches to pulmonary function testing that aid the diagnosis and monitoring of lung diseasessuch as Asthma and COPD.

We are launching the next generation of our product and are therefore seeking to add an engaged and motivated:

SENIOR MACHINE LEARNING DEVELOPER

As a Machine Learning Developer, you will be responsible for the design, development, validation, and deployment of machine learning algorithms supporting our medical devices and digital health solutions. You will work closely with clinical, software, systems, and regulatory teams to transform data into actionable insights and innovative diagnostic capabilities.

Specific tasks include:

• Develop, train, evaluate, and optimize machine learning and artificial intelligence models for medical applications.
• Analyze clinical, physiological, and device-generated datasets to identify trends, patterns, and opportunities for improving product performance.
• Design data preprocessing, feature engineering, and model validation pipelines.
• Collaborate with software and systems engineers to integrate machine learning algorithms into commercial products.
• Establish metrics and validation procedures to ensure model robustness, accuracy, and clinical relevance.
• Document development activities in compliance with quality management system requirements.
• Support the verification and validation of software and machine learning components.
• Contribute to the creation and maintenance of technical documentation required for regulatory submissions.
• Participate in the definition of data collection strategies and clinical study requirements to support algorithm development.
• Monitor advancements in artificial intelligence, machine learning, and medical technology to identify opportunities for innovation.
• Provide technical expertise and guidance to multidisciplinary project teams.
• Support risk management activities related to machine learning systems and software functionality.
• Define and maintain the post-market monitoring strategy for machine learning models, including performance and data drift monitoring, alert thresholds, periodic reassessment, retraining criteria, rollback procedures, and incident management.
• Define, document, and implement cybersecurity requirements for AI/ML-enabled medical devices in alignment with Good Machine Learning Practice principles and applicable Health Canada, FDA, and other market-specific regulatory expectations

As for all THORASYS employees, prioritizing and upholding high standards of security and data privacy in accordance Thorasys procedures and policies.

Competencies and Qualifications

• Machine Learning & AI: Strong understanding of supervised and unsupervised learning, deep learning, model evaluation, and optimization techniques.
• Data Analysis: Ability to work with large and complex datasets and extract meaningful insights.
• Programming: Proficiency in Python and common machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Software Development: Familiarity with software development best practices, version control, and testing methodologies.
• Problem Solving: Ability to translate clinical and business needs into technical solutions.
• Communication: Ability to explain complex technical concepts to both technical and non-technical stakeholders.
• Collaboration: Ability to work effectively within multidisciplinary teams.
• Knowledge of regulatory environments such as ISO 13485, IEC 62304, FDA guidance on Software as a Medical Device (SaMD), and AI/ML-enabled medical devices is highly desirable.
• Experience with cloud computing, MLOps, and data engineering tools is an asset.
• Fluency in English (and preferably French), spoken and written.

Education and experience

• University degree in Computer Science, Software Engineering, Biomedical Engineering, Data Science, Artificial Intelligence, or a related field.
• Master's degree or PhD in Artificial Intelligence, Machine Learning, Data Science, or a related discipline is an asset.
• 5-10 years of experience developing and deploying machine learning solutions in a professional environment.
• Experience in a regulated industry such as medical devices, healthcare, aerospace, or pharmaceuticals is an asset.
• Experience working with clinical, physiological, biomedical, or other scientific datasets is highly desirable.

Report

Unless designated otherwise by the CEO you will report to the VP R&D.