Wave HQ
Machine Learning Engineer
Canada · Mid
Sponsorship not specifiedCAD 101k-CAD 113kDetected 91 days ago
SnowflakeDatabricksAWSMachine LearningSparkAirflowData ScienceMLOpsRecruitingCommunicationMentoring
About the role
- We work in an environment buzzing with creative energy and inspiration.
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.
- You thrive in ambiguous conditions by independently identifying opportunities to optimize model pipelines and improve AI workflows.
- Partner with data scientists, product managers, and software engineers to translate business needs into technical requirements and integrate AI solutions into production applications.
Requirements
- No matter where you are or how you get the job done, you have what you need to be successful and connected.
- The mark of true success at Wave is the ability to be bold, learn quickly and share your knowledge generously.
- At least 3 years of hands-on experience with AWS infrastructure, specifically SageMaker, Spark/AWS Glue, and Infrastructure as Code (IaC) using Terraform.
- High proficiency in managing multi-stage workflows using Airflow or similar orchestration systems to automate training and deployment cycles.
- Familiarity with model governance practices (lineage, fairness, and privacy) and experience using data cataloging tools for compliance.
- Strong ability to communicate complex technical concepts to non-technical stakeholders and influence project direction.
Skills
- You Thrive Here By Possessing the Following:
Compensation
- CAD 101k-CAD 113k
Company info
- At Wave, we value diversity of perspective.
Apply directly at Wave HQ →Create a free account for alerts like thisView Wave HQ immigration profile
This listing is sourced directly from Wave HQ's careers page and normalized into a canonical job model.