Job Description: Machine Learning Engineer
Location
- Hybrid role based out of Newmarket office 3 days a week (Monday to Wednesday)
Role Summary
We're seeking a Machine Learning Engineer with a strong focus on MLOps to join our expanding team. In this role, you'll manage the entire infrastructure and automation of ML pipelines, focusing on deployment, scaling, monitoring, and maintaining real-time and batch machine learning workflows in production.
Collaborations
- Work 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 the entire ML lifecycle.
- Develop infrastructure and tools for continuous integration, testing, deployment, and retraining of ML models.
- Implement and operate feature stores, model registries, and orchestration frameworks.
- Deploy and serve ML models in low-latency, high-throughput environments using containerized microservices.
- Implement monitoring systems for model performance, data quality, and operational health.
- Build automated alerting and dashboarding for system visibility.
- Ensure model traceability, auditability, and governance.
- Optimize cloud infrastructure on AWS using Infrastructure as Code.
- Be available for occasional on-call duties over weekends in case of incidents.
Required Qualifications
- 2+ years experience as a Machine Learning or MLOps Engineer.
- 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).
- Familiarity with monitoring and observability tools (Grafana, CloudWatch, Opsgenie, Datadog).
- Experience with streaming and batch data systems (Spark, PySpark, Kinesis).
- Strong problem-solving and cross-functional communication skills.
Perks & Benefits
- Health, Dental, and Life insurance benefits.
- Three weeks paid vacation, birthdays off, and five personal days.
- Employer RRSP matching contributions (limited conditions apply).
- Discounted Employee Share Purchase Plan.
- Mental health and wellbeing resources, including professional therapy, meditation, and health resources.
Diversity & Inclusion
- Committed to creating an inclusive, accessible workplace and encouraging diversity.
- Adjustments available for people with disabilities or health conditions upon request.
Additional Notes
- Responsibilities are general and may change. This does not restrict the Company’s right to reassign duties.
Job Highlights
Focus on MLOps, Cloud-based deployment, Real-time & Batch ML pipelines, AWS, Docker, Kubernetes
Summary
- Role based out of Newmarket with a focus on ML infrastructure.
- Responsibilities include pipeline management, model deployment, environment optimization.
- Collaborate across teams, working on scalable ML solutions.
Perks
- Inclusive benefits package, mental health resources, flexible work.