
Machine Learning Engineer
Posted 1 day ago

Posted 1 day ago
This is a fully remote position, open to applicants in Canada.
• Design, develop, train, and implement foundational AI and machine learning models within production settings.
• Create robust and scalable machine learning pipelines and platforms that facilitate advanced analytics and business intelligence.
• Champion high standards in coding, testing, and MLOps processes.
• Develop resilient and cost-effective ML and AI applications while scaling modern systems.
• Work in partnership with risk specialists, product leads, and software developers to translate strategic requirements into technical specifications and integrate ML features into live applications.
• Ensure model reliability, fairness, compliance, lineage tracking, and data protection measures are in place.
• Create observability systems that monitor model health and operational metrics while assessing organizational value.
• A minimum of 3–5 years of professional experience in machine learning engineering.
• Demonstrated success in deploying machine learning models in production environments.
• Comprehensive understanding of the modern data stack and data ingestion workflows.
• Experience with Databricks or Redshift.
• At least 3 years of practical experience with AWS infrastructure, including SageMaker, Spark/AWS Glue, and Terraform.
• High proficiency in Airflow or similar orchestration systems.
• Hands-on experience with MLflow, Kubeflow, or SageMaker Feature Store.
• Familiarity with model governance practices encompassing lineage, fairness, and privacy.
• Experience with data cataloging tools for compliance purposes.
• Strong ability to convey complex technical concepts to non-technical stakeholders and steer project direction.
• Experience in FinTech or Financial Risk is a significant plus.
• Bonus Structure
• Employer-paid Benefits Plan
• Health & Wellness Flex Account
• Wellness Days
• Paid Holiday Shutdown
• Wave Days (extra vacation days in the summer)
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