Machine Learning Engineer II
CanadaFull-TimeMiddle
Salary$101,000 - $113,000 a year
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Job Details
- Experience
- 4–6 years
- Required Skills
- AWSMachine LearningSnowflakeAirflowSparkTerraformRedshiftDatabricksMLOps
Requirements
- Minimum of 4–6 years of professional experience in machine learning engineering, with a proven track record of deploying models into production environments.
- Degree/Diploma in Computer Science, Engineering, Data Science, Applied AI, Machine Learning, or related field.
- Deep understanding of the modern AI stack, including data ingestion workflows.
- Experience working with curated data warehouses like Snowflake, Databricks, or Redshift.
- At least 3 years of hands-on experience with AWS infrastructure (SageMaker, Spark/AWS Glue).
- Experience with Infrastructure as Code (IaC) using Terraform.
- High proficiency in managing multi-stage workflows using Airflow or similar orchestration systems.
- Practical experience with MLOps tools such as MLflow, Kubeflow, or SageMaker Feature Store.
- Familiarity with model governance practices (lineage, fairness, privacy) and data cataloging tools.
- Strong ability to communicate complex technical concepts to non-technical stakeholders.
- Experience in FinTech or SaaS environments is a significant advantage.
Responsibilities
- Take ownership of the design and implementation of modern AI stack components, including data ingestion for AI/ML workloads and end-to-end model training and serving pipelines.
- Build and manage fault-tolerant AI platforms that scale economically.
- Provide technical mentorship to junior engineers and foster a collaborative environment.
- Promote best practices in coding, testing, and MLOps.
- Partner with data scientists, product managers, and software engineers to translate business needs into technical requirements.
- Enforce model quality standards, integrity, and reliability, including model lineage, fairness, and privacy controls.
- Build monitoring frameworks to track model performance and system KPIs.
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