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Machine Learning Engineer II

1 month, 3 weeks ago
Canada
Full-time
Senior
Machine Learning Engineer
Software Development
Apache Airflow Apache Spark AWS Databricks Kubeflow Machine Learning MLflow MLOps Snowflake Terraform
Apply Now
Wave

Wave

Wave is a small business software company that offers a suite of money management tools including invoicing, accounting, credit card processing, payroll, receipt scanning, and personal finance tools. With 2.5 million customers worldwide, Wave provides ...

Internet Software & Services
251-1K
Founded 2010
$80M raised
View All Jobs 8

Description

  • Design and implement modern AI stack components, including data ingestion for AI/ML workloads and end-to-end training and serving pipelines.
  • Build and manage fault-tolerant, scalable AI platforms that support efficient model development and deployment.
  • Maintain legacy models while developing new scalable machine learning solutions.
  • Provide technical mentorship to junior engineers and foster collaboration across the team.
  • Act as a bridge between data science and production engineering.
  • Promote best practices in coding, testing, and MLOps.
  • Partner with data scientists, product managers, and software engineers to translate business needs into technical requirements.
  • Integrate AI solutions into production applications.
  • Implement model governance controls, including lineage, fairness, privacy, and quality standards.
  • Build monitoring frameworks to track model performance, system KPIs, and business outcomes.

Requirements

  • 4–6 years of professional experience in machine learning engineering with a track record of deploying models into production.
  • Degree or diploma in Computer Science, Engineering, Data Science, Applied AI, Machine Learning, or a related combination.
  • Deep understanding of the modern AI stack, including data ingestion workflows and curated data warehouses such as Snowflake, Databricks, or Redshift.
  • At least 3 years of hands-on AWS experience, specifically with SageMaker, Spark/AWS Glue, and Infrastructure as Code using Terraform.
  • High proficiency with multi-stage workflow orchestration using Airflow or similar systems.
  • Practical experience with MLflow, Kubeflow, or SageMaker Feature Store.
  • Familiarity with model governance practices, including lineage, fairness, and privacy, and experience with data cataloging tools for compliance.
  • Strong communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
  • Experience in FinTech or SaaS environments is a significant advantage.

Benefits

  • $101,000–$113,000 annual salary, with final compensation based on experience and role alignment.
  • Bonus structure.
  • Employer-paid benefits plan.
  • Health and wellness flex account.
  • Professional development account.
  • Wellness days and paid holiday shutdown.
  • Wave Days, providing extra vacation days in the summer.
  • Get A-Wave program, allowing work from anywhere in the world for up to 90 days.

Interested in this position?

Apply directly on the company website

Apply Now

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