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Posted 3 months ago

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Platform Engineer, Machine Learning

TorontoRemoteContract

AI Summary

Senior ML Platform Engineer (Contract) builds and scales ML platforms, developing Databricks and Spark pipelines, extending platform capabilities, and supporting MLOps workflows in cloud environments for financial services clients.

About this role

RAVL is a boutique technology advisory and engineering firm focused on the financial services industry. Everything we do is centered on helping our clients realize measurable ROI from their technology investments.

We’re hiring Senior ML Platform Engineers (Contract) to contribute to building and scaling machine learning platforms across a range of client engagements. This work includes developing ML pipelines, extending platform capabilities, and supporting MLOps workflows in cloud environments.

These roles support both active delivery and upcoming opportunities, offering the chance to work on modern, production-grade ML systems.

What does success look like in this role?

  • Build and extend ML platform components on Databricks
  • Develop ML pipelines for training, deployment, and monitoring
  • Implement reusable workflows aligned with platform architecture
  • Integrate with enterprise tooling and services
  • Support performance, reliability, and observability
  • Great, do my skills fit?

  • Strong Databricks and Spark experience
  • Experience building ML pipelines and workflows
  • Proficiency in Python
  • Cloud experience (Azure preferred)
  • Familiarity with CI/CD and automation
  • Nice to have skills

  • MLflow or similar tools
  • Enterprise integration experience
  • Mindset Traits

    • Strong builder and problem solver
    • Detail-oriented and delivery-focused
    • Collaborative

    Why join RAVL?

  • Flexible, client-aligned work model — autonomy with accountability, adapting to client delivery needs
  • Variable bonus & RRSP contributions tied to performance and delivery impact.
  • 4 weeks paid time off (plus public holidays)
  • Paid professional development days and continuous learning opportunities
  • Comprehensive health & dental coverage, including mental health support
  • Commitment to lifelong learning — continuous improvement through training, mentorship, and certification
  • Skills

    AutomationAzureCI/CDDatabricksMLflowML PipelinesPythonSpark

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