lever
Machine Learning Engineer
Waveapps
Remote, CAN
Full-time
Mid · 3+ years experience
Remote
CAD 100000-130000 yearly / year
Discovered 3 weeks ago
AWSSageMakerSparkAWS GlueTerraformAirflow
Free
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Key Skills for This Role
AWSSageMakerSparkAWS GlueTerraformAirflow
Full Job Posting
- Bonus Structure
• Health & Wellness Flex Account
- Wellness Days
• Paid Holiday Shutdown
- Wave Days (extra vacation days in the summer)
- Develop & Deploy: Focus on the hands-on building, training, and operational deployment of machine learning models, ensuring they perform reliably within existing production environments.
- Champion Technical Standards: Advocate for top-tier practices across coding, testing, and MLOps processes. Navigate ambiguity autonomously to refine pipelines and elevate ML engineering workflows.
- Optimize & Scale: Construct resilient, cost-efficient ML & AI use cases. Balance sustaining established models with accelerating the rollout of highly scalable, modern systems.
- Partner & Collaborate: Team up with cross-functional stakeholders, including risk specialists, product leads, and software developers, to convert strategic needs into technical specs and smoothly embed ML features into live applications.
- Establish Controls & Governance: Uphold stringent benchmarks for model dependability, fairness, and compliance. Direct the integration of lineage tracking and data protection workflows into our automated systems.
- Track & Evaluate: Formulate comprehensive observability systems to capture model health and key operational metrics, ensuring machine learning investments yield quantifiable organizational value.
- Experience: Minimum of 3–5 years of professional experience in machine learning engineering, with a proven track record of deploying models into production environments.
- Technical Depth: Deep understanding of the modern data stack, including data ingestion workflows and experience working with curated data warehouses like Databricks or Redshift .
- Cloud Proficiency: At least 3 years of hands-on experience with AWS infrastructure , specifically SageMaker , Spark/AWS Glue, and Infrastructure as Code (IaC), Terraform .
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