Machine Learning Engineer

Description

Machine Learning Engineer

The hybrid role will be based out of our Newmarket office 3 days a week (Mon-Wed)

We’re looking for a Machine Learning Engineer with a strong focus on MLOps to join our growing team. In this role, you'll own the end-to-end infrastructure and automation of ML pipelines, with a focus on deploying, scaling, monitoring, and maintaining real-time and batch machine learning workflows in production environments.

You’ll collaborate closely with data scientists, IT, and platform teams to ensure ML models are production-ready, reliable, and observable at scale.

Key Responsibilities

• Design, build, and maintain real-time and batch ML pipelines supporting end-to-end ML lifecycle.
• Develop infrastructure and tooling for continuous integration, testing, deployment, and retraining of ML models.
• Implement and operate feature stores, model registries, and orchestration frameworks for reproducible ML workflows.
• Deploy and serve ML models in low-latency and high-throughput production environments using containerized microservices.
• Implement robust monitoring systems for Model Performance, Data quality, and Operation health.
• Build automated alerting and dashboarding for visibility into ML system health.
• Ensure model traceability, auditability, and governance practices.
• Optimize infrastructure on cloud platforms (AWS) using Infrastructure as Code.
• As part of our ML operation team, this role will be responsible to occasionally be on call over the weekends in the events of incidents.
  
  

Required Qualifications

• 2+ years of experience as a Machine Learning Engineer, MLOps Engineer, or related role.
• Proficiency in Python and ML libraries (e.g., scikit-learn,…)
• Experience with MLOps frameworks and tools
• Strong understanding of containerization and deployment (Docker, Kubernetes).
• Proficiency with AWS and IaC tools (Terraform, CloudFormation).
• Experience with monitoring and observability stacks ( Grafana, CloudWatch, Opsgenie, Datadog).
• Familiarity with streaming and batch data systems ( Spark, PySpark, Kenises).
• Excellent problem-solving and communication skills; comfortable working cross-functionally.
  
  

Perks & Benefits

• Health, Dental, and Life Benefits
• 3 weeks paid vacation, birthdays off and 5 personal days
• Matched employer RRSP contribution (subject to limits)
• Discounted Euronet Employee Share Purchase Plan (ESPP)
• Plumm Mental Health and Wellbeing and offers access to professional therapists, meditation, and resources to focus on your overall health
  
  

We want Xe to be a great place to work and to ensure that our communities are represented across our workforce. A vital part of this is ensuring we are a truly inclusive organization that encourages diversity in all respects.

At Xe we are committed to making our recruitment practices barrier-free and as accessible as possible for everyone. This includes making adjustments or changes for disabled people, neurodiverse people or people with long-term health conditions. If you would like us to do anything differently during the application, interview or assessment process, including providing information in an alternative format, please contact us on [email protected]

The position responsibilities outlined above are intended to define the general contents and requirements to perform this job. It is not to be taken as a complete statement of responsibilities or requirements. This job description does not restrict the Company’s right to assign or reassign duties and responsibilities to this job as needed.