MLOps, Data Engineer

This is a fully remote position, open to applicants in Canada.

📋 Description

• Design, implement, and maintain CI/CD pipelines for machine learning workflows utilizing tools such as GitHub Actions, Azure DevOps, or Jenkins.

• Construct and enhance data processing pipelines in Apache Spark (using PySpark and Scala) for large-scale, distributed listener datasets.

• Deploy and oversee Databricks environments, ensuring optimal cluster usage, job scheduling, and cost efficiency.

• Collaborate with data scientists to transition ML models to production, integrating them into scalable APIs or batch processing systems that deliver real-time, machine-readable audience signals.

• Establish automated testing, monitoring, and alerting for ML pipelines to guarantee reliability and reproducibility.

• Advocate for best practices in version control, model registry management, and environment reproducibility.

• Assist in evolving listener data infrastructure towards agent-compatible supply with live, structured, queryable data feeds.

⛳️ Requirements

• Demonstrated experience in Data Engineering, MLOps, and DevOps positions with an emphasis on automation and scalability.

• Strong programming abilities in Python, with practical experience in Apache Spark.

• Proficiency in Scala is a significant advantage.

• In-depth knowledge of Databricks, including Delta Lake, structured streaming, and feature engineering.

• Comprehensive understanding of CI/CD principles and tools (e.g., GitHub Actions, Jenkins, Azure DevOps, GitLab CI, ArgoCD).

• Familiarity with cloud platforms (AWS, Azure, or GCP) for data and ML workloads.

• A problem-solving approach and the capability to work collaboratively with cross-functional teams.

• Strong architectural perspective, able to assess trade-offs related to cost, performance, scalability, and maintainability when choosing tools and designing systems.

• Experience with containerized and orchestrated environments (Kubernetes / OpenShift), including deployment, scaling, and fault tolerance of data and ML workloads.

• Advanced proficiency in English is required.

• Knowledge of French is an asset.

• Familiarity with IAB data standards, programmatic advertising infrastructure, or AdTech data pipelines is a strong advantage.

🏝️ Benefits

• Fully remote position (candidates must be located in ONTARIO or QUEBEC).

• 4 weeks of vacation plus 5 paid personal days each year.

• Group insurance programs available from your first day, including access to telemedicine and an Employee Assistance Program (EAP).

• Collective RRSP with matching contributions.

• Internet reimbursement.