Senior Machine Learning Engineer

Our client is an AI-first healthcare startup building clinical decision-support tools used by hospitals across Canada. They're looking for a Senior ML Engineer to own the model development lifecycle — from research through to production deployment — working closely with a small team of world-class engineers and clinicians. As a Senior ML Engineer, you will own the end-to-end model development lifecycle for clinical prediction systems. You will collaborate with healthcare clinicians to translate complex clinical requirements into robust ML architectures. Staying hands-on, you will design, train, and validate ML pipelines, ensure model reliability, and scale deployments to production environments. Additionally, you will establish best practices for testing, experiment tracking, and model monitoring in hospital networks.

Why This Role

You'll build clinical decision-support models directly impacting patient lives across Canada, solving genuine ML validation and safety challenges on sensitive healthcare data.

What You'll Do:

• Design, train, and iterate on deep learning models for clinical prediction tasks.
• Build and maintain scalable ML data pipelines and model inference infrastructure.
• Partner with clinical teams to integrate domain knowledge and clinical signals into features.
• Establish robust model evaluation, validation, and real-time monitoring standards in production.

What You'll Bring:

• 5+ years of software engineering experience focusing on machine learning and applied AI.
• Deep proficiency in Python and modern ML frameworks like PyTorch or TensorFlow.
• Hands-on experience deploying and scaling ML models within production cloud environments.
• Solid foundation in data engineering, preprocessing, and model validation techniques.

It's a bonus if you have:

• Prior experience with clinical medical data (EHR, FHIR, HL7).
• Familiarity with MLflow or Weights & Biases for experiment tracking.