Machine Learning Engineer

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

1. Design, build, and maintain real-time and batch ML pipelines supporting end-to-end ML lifecycle.
2. Develop infrastructure and tooling for continuous integration, testing, deployment, and retraining of ML models.
3. Implement and operate feature stores, model registries, and orchestration frameworks for reproducible ML workflows.
4. Deploy and serve ML models in low-latency and high-throughput production environments using containerized microservices.
5. Implement robust monitoring systems for Model Performance, Data quality, and Operation health.
6. Build automated alerting and dashboarding for visibility into ML system health.
7. Ensure model traceability, auditability, and governance practices.
8. Optimize infrastructure on cloud platforms (AWS) using Infrastructure as Code.
9. 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

1. 2+ years of experience as a Machine Learning Engineer, MLOps Engineer, or related role.
2. Proficiency in Python and ML libraries (e.g., scikit-learn,…).
3. Experience with MLOps frameworks and tools.
4. Strong understanding of containerization and deployment (Docker, Kubernetes).
5. Proficiency with AWS and IaC tools (Terraform, CloudFormation).
6. Experience with monitoring and observability stacks (Grafana, CloudWatch, Opsgenie, Datadog).
7. Familiarity with streaming and batch data systems (Spark, PySpark, Kinesis).
8. Excellent problem-solving and communication skills; comfortable working cross-functionally.

Perks & Benefits

1. Health, Dental, and Life Benefits.
2. 3 weeks paid vacation, birthdays off and 5 personal days.
3. Matched employer RRSP contribution (subject to limits).
4. Discounted Euronet Employee Share Purchase Plan (ESPP).
5. 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.