Machine Learning Engineer
New
W
WaveFinTech
CanadaFull-TimeMiddle
Salary$100,000 - $130,000 a year
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Job Details
- Experience
- 3–5 years
- Required Skills
- AWSMachine LearningMLFlowAirflowSparkTerraformRedshiftDatabricksMLOps
Requirements
- 3–5 years of professional machine learning engineering experience.
- Proven track record of deploying models into production environments.
- Deep understanding of the modern data stack and data warehouses (e.g., Databricks or Redshift).
- 3+ years of hands-on experience with AWS infrastructure (SageMaker, Spark/AWS Glue).
- Experience with Infrastructure as Code (Terraform).
- High proficiency in managing workflows using Airflow or similar orchestration systems.
- Practical experience with MLOps tools such as MLflow, Kubeflow, or SageMaker Feature Store.
- Familiarity with model governance, lineage, fairness, and privacy practices.
- Ability to communicate complex technical concepts to non-technical stakeholders.
- Experience in FinTech or Financial Risk environments is a significant advantage.
Responsibilities
- Develop and operationalize machine learning models for production environments.
- Advocate for and implement MLOps best practices, coding standards, and testing processes.
- Optimize and scale ML systems for cost-efficiency and performance.
- Collaborate with risk specialists, product leads, and developers to embed ML features into live applications.
- Establish model governance, lineage tracking, and data protection controls.
- Design observability systems to monitor model health and performance metrics.
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