Unknown company
Lead / Senior Machine Learning Engineer
Summary
Build and deploy production-grade ML models and MLOps pipelines for a credit union, focusing on forecasting, personalization, and automation using Python, Azure ML, and Databricks.
- Applying Data Science and Machine Learning best practices to develop robust models and support data-driven decision-making across business domains
- Applying machine learning and data science techniques such as forecasting, predictive modeling, classification, regression, recommendation, and optimization to solve business problems
- Conducting experiments and evaluating models using appropriate statistical, technical, and business performance metrics
- Architecting, building, deploying, and maintaining scalable machine learning models and AI solutions integrated into enterprise systems, applications, and operational workflows
- Designing and implementing end-to-end ML workflows, including data preparation, feature engineering, model training, validation, deployment, optimization, and continuous monitoring in a high-scale production environment
- Developing reusable machine learning components, feature pipelines, and model-serving frameworks to support multiple use cases and teams
- Designing and implementing production-grade MLOps solutions using Azure ML, Databricks, MLflow, and related cloud technologies
- Building and maintaining automated ML pipelines, feature engineering workflows, feature store patterns, and deployment processes for training, testing, monitoring, and retraining machine learning models
- Implementing standards and best practices for model versioning, lifecycle management, governance, deployment automation, model performance monitoring, drift detection, data quality, operational health, and retraining triggers
- Developing production-quality Python code, APIs, automation workflows, and machine learning services to integrate ML capabilities into business applications and processes
- 10+ years of experience in Machine Learning Engineering, Data Science, Applied AI, Software Engineering, or related disciplines
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Mathematics, Statistics, or a related quantitative field
- Strong hands-on experience building and deploying cloud-based applications and machine learning services
- Strong proficiency in Python and SQL, with solid software engineering fundamentals including data structures, algorithms, and object-oriented design
- Hands-on experience with industry-standard machine learning and deep learning frameworks such as PyTorch, TensorFlow, and Scikit-learn
- Proven experience productionizing machine learning models and operating scalable, reliable ML systems in enterprise environments
- Hands-on experience with Azure Machine Learning, Databricks, MLflow, CI/CD pipelines, model lifecycle management, monitoring, and deployment automation
- Strong understanding of API design and service integration, machine learning algorithms, statistical modeling, feature engineering, and model evaluation techniques
- Proven ability to take solutions from prototype to production
- Exposure to machine learning use cases such as churn prediction, forecasting, predictive modeling, member or customer personalization, recommendation systems, marketing optimization, and experimentation frameworks such as A/B testing
- Familiarity with advanced machine learning techniques including anomaly detection, graph neural networks, optimization methods, representation learning, causal inference, and Generative AI workflows
- Experience integrating AI services into automation platforms such as UiPath or Power Automate and familiarity with AWS, GCP, Power BI, or Tableau
- Production-Focused – You measure success by scalable, reliable, and production-ready machine learning solutions
- Hands-On – You enjoy designing, building, deploying, and operationalizing machine learning solutions from end to end
- Collaborative – You work effectively with data, platform, cloud, security, and business teams to deliver meaningful outcomes
- Technically Curious – You continuously explore emerging technologies, machine learning techniques, and AI innovations
- Quality-Driven – You prioritize engineering excellence, automation, testing, monitoring, and maintainable code
- Living Wage Employer: We’re the largest private-sector Living Wage Employer in Canada and consistently ranked among Canada’s Top Employers
- Customizable Benefits: Permanent employees receive flexible benefit packages that can be tailored annually to meet evolving needs
- Generous Vacation: New employees start with 3-4 weeks of vacation per year, with additional days earned over time
- Extra Stat Holidays: In addition to BC’s 11 statutory holidays, we offer 2 extra days, plus care days for personal or family illness
- Immediate Health Coverage: Health and dental benefits begin on your hire date, with three levels of coverage to choose from
- Defined Benefit Pension: Our retirement plan provides a guaranteed income for life, recognizing that retirement looks different for everyone