Jobs › Companies › Medcan › Associate Machine Learning Engineer

About this Associate Machine Learning Engineer role at Medcan

Medcan · Onsite · Toronto

Are you passionate about helping people live their healthiest lives? Do you thrive in a dynamic, supportive environment where your contributions truly matter? If so, Medcan is the place for you!


This job is for a current vacancy.


 

About the Role

Medcan is seeking a motivated and hands-on Associate Machine Learning Engineer to support the development and delivery of innovative machine learning, AI, optimization, and analytics solutions that improve operational efficiency and decision-making across the organization.


This role provides an excellent opportunity to work on real-world ML, AI and analytics initiatives, including resource forecasting, optimization and scheduling, conversational analytics, AI agents, and enterprise AI applications. The successful candidate will work under the guidance of senior technical leadership while gaining practical experience across machine learning implementation, software engineering, testing and validation, UI development, governance, auditability, and cloud-based solution delivery.


What You'll Do


ML / AI Development and Testing

  • Develop, test, and enhance machine learning, forecasting, optimization, analytics, and AI pipelines.
  • Support the design, implementation, and validation of AI agents, conversational AI, Retrieval-Augmented Generation (RAG), MCP tools and agent orchestration workflows.
  • Perform feature engineering, model evaluation, performance testing, and business rule validation to ensure solution quality and accuracy.
  • Integrate enterprise data sources, APIs, tools, and model outputs into AI and analytics applications.
  • Design and execute testing activities including functional, integration, regression, ML model drift, RBAC, auditability, and governance validation.
  • Contribute to reusable AI components, solution prototyping, troubleshooting, documentation, and continuous improvement of production-ready solutions. 

Software Development Lifecycle

  • Design, develop, test, and maintain production-quality ML, AI, analytics, and user-facing applications using Python and modern software engineering practices.
  • Build reusable, modular, and maintainable components, dashboards, and business-facing tools while following coding standards, code review processes, and source control best practices.
  • Support debugging, root-cause analysis, performance optimization, CI/CD processes, release management, and production readiness activities.
  • Enhance application usability, user experience, documentation, and continuous improvement of ML and AI solutions. 

Collaboration & Learning

  • Work closely with business stakeholders, product owners, architects, and ML/AI engineers.
  • Participate in brainstorming sessions and design discussions for future ML/AI initiatives.
  • Contribute to solution reviews, code reviews, and technical workshops.
  • Continuously learn and apply industry best practices in machine learning, software engineering, and ML/AI technologies.

 What You'll Need


  • Bachelor's or master’s degree in computer science, Data Science, Engineering, Mathematics, Statistics, or a related field.
  • 1-3 years of experience in software development, analytics, machine learning, AI, or related technical disciplines.
  • Strong Python programming skills and experience with data analysis using Python libraries such as Pandas and NumPy.
  • Understanding of machine learning concepts, model evaluation techniques, and predictive analytics.
  • Experience using SQL for data analysis, validation, and troubleshooting.
  • Strong problem-solving and analytical thinking skills.
  • Excellent written and verbal communication skills.

Preferred Qualifications
 

Machine Learning & AI

  • Experience with Scikit-Learn, XGBoost, CatBoost, or similar machine learning frameworks.
  • Knowledge of forecasting, optimization, scheduling, or decision-support solutions.
  • Experience with Microsoft Azure AI and data services, including Azure Machine Learning, Azure OpenAI, Azure AI Foundry, MLOps/CI-CD, and deploying secure, scalable AI/ML solutions in the cloud.
  • Understanding of Generative AI, Large Language Models (LLMs), and AI agents.
  • Familiarity with Retrieval-Augmented Generation (RAG) concepts, MCP tools and conversational AI applications.
  • Experience evaluating AI agent performance and model outputs.

API & Backend Development (Nice to Have)

  • Experience with Streamlit, Dash, Gradio, or similar Python UI frameworks.
  • Experience developing or integrating REST APIs.
  • Familiarity with FastAPI, Flask, or similar Python backend frameworks.
  • Experience working with JSON-based APIs and service integrations.
  • Understanding of API authentication, authorization, and secure integration practices.
  • Exposure to backend service or microservice development.

Domain Experience (Nice to Have)

  • Interest in operations research, optimization, scheduling, healthcare analytics, or enterprise AI applications.

Position Pay Range

$71,465.00 - $98,264.75 CAD annually

 

Pay will be determined based on an analysis of the selected candidate's experience and qualifications within the role's compensation grade. Medcan's compensation ranges are determined by a combination of required qualifications and skills, market value, and internal equity. The above range pertains solely to the base compensation and is not inclusive of additional compensation details such as perks, benefits, and potential bonuses or incentives. 

 

​Notice to Candidates: Recruitment Fraud 

Please note that Medcan will never request any form of payment from candidates at any stage of the recruitment or hiring process. In addition, Medcan does not utilize third-party immigration consultants or recruitment agents to conduct offers of employment on our behalf. Employment contracts are shared directly by members of the Medcan Talent Acquisition or Human Resources team using official Medcan email domains.

If you receive a request for payment or are contacted by an individual or organization claiming to represent Medcan that appears suspicious, please do not respond or share personal information. Instead, we encourage you to contact us directly at [email protected] to verify the legitimacy of the communication.

 

Diversity, Equity and Accessibility:

Medcan is dedicated to equity, diversity and inclusion. We strive to ensure all stakeholders have a fair opportunity to participate in our community. If contacted for an opportunity, please advise your Talent Acquisition contact should you require accommodation.

 

AI Use Disclosure – Opportunities at Medcan

Medcan uses artificial intelligence (AI) tools to support the screening and assessment of applicants for opportunities as part of a fair, transparent, and inclusive process. These tools assist our team but do not make final decisions. All decisions are reviewed and made by our teams to ensure fairness and alignment with Medcan’s values. If you have questions about how your application is assessed, please contact the Medcan Talent Acquisition team at [email protected].

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How this ML Engineer salary compares

This role pays $60,115/yr — below the typical range for ML Engineer roles.

$86,137 median $142,459 $279,570

Typical range $108,120–$212,253/yr, from 43 comparable ML Engineer listings on JobsRadar (pay annualized to USD). See ML Engineer salary insights →

About Medcan

Medcan is a global leader in proactive health and wellness services and is devoted to providing care that is grounded in the latest evidence-based practices, technologies and treatments. Our team includes physicians, clinicians, allied health, administrative and corporate professionals that are passionate about supporting individuals, families and employers to live well, for live . Medcanners are client obsessed, our business is powered by people, and we believe in challenging the status quo and focusing on what matters. We value excellence, drive, respect and integrity. Medcan's head office is located at 150 York Street in downtown Toronto , with additional locations across Ontario. Learn m

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