Act as the bridge between backend engineering, data science, and operations — ensuring that forecasting models, optimization solvers, and data-driven decision flows are not only theoretically correct but also reliable and observable in production.
Design and maintain data pipelines, data architectures, and experimentation tools that enable rapid iteration, high reliability, and continuous improvement of our planning intelligence.
Build and maintain continuous learning pipelines—automated training pipelines for ML forecasting models that incorporate new data and guardrails against performance drift.
Create reproducible CI workflows for ML models and CP-SAT solver configurations, including automated regression checks and benchmarking.
Develop and manage real-time and batch inference pipelines that feed appointment demand forecasts and provider scheduling decisions.
Implement robust observability—structured logging, metrics, tracing, and alerts—to ensure models and solvers behave as expected in production.
Enable a short research loop by designing tools and data flows that allow data scientists and engineers to experiment, compare model variants, and deploy improvements with confidence.
Requirements
Experience building and operationalizing ML training and inference pipelines using modern data engineering and MLOps tools.
Experience working with mathematical optimization tools (e.g., OR-Tools/CP-SAT, Pyomo, Gurobi) and understanding how to validate, benchmark, and put solver logic into production.
Strong software engineering fundamentals—version control, CI/CD, testing, observability, and infrastructure as code.
Comfortable collaborating closely with data scientists, backend engineers, and operational stakeholders in a cross-functional product environment.
Care as much about reliability and correctness as about speed, and enjoy building simple, maintainable, and measurable systems.
Thrive in environments where your work directly informs real operational decisions.
Benefits
Access to the Dialogue app and virtual mental health support for you and your family
Fully covered insurance, health spending account, dental coverage, and wellness reimbursement
4 weeks of vacation, 9 wellness days, and 1 volunteer day
Hybrid work: 3 days/week in our Montreal or Toronto offices (except for fully remote roles)
Option to work abroad for up to 4 weeks per year
Incentive programs, referral bonuses, and RRSP matching
Learning via Coursera, external training budget, and a mentorship program
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