Senior Machine Learning Engineer Job Toronto Ontario Canada,IT/Tech

The Role

Senior ML Engineer (MLOps)

Rakuten Kobo Inc. is seeking a visionary and highly skilled Senior ML Engineer to spearhead the evolution of our MLOps capabilities. In this pivotal role, you will collaborate closely with Data Scientists, Data Engineers, Platform Engineers, and business stakeholders to transform our Machine Learning production workflows from manual processes to a state-of-the-art, fully automated framework on the Google Cloud Platform (GCP).

This groundbreaking position is dedicated to streamlining the entire ML project lifecycle, ensuring the continuous delivery of significant business value through innovative Machine Learning solutions. Success in this role demands not only profound ML engineering expertise but also a forward-thinking mindset for seamlessly integrating ML/AI into the core of our engineering practices.

Experience and Background:

Bachelor's degree in Computer Science, Engineering, or a related discipline; master's degree is preferred.

5+ years in ML Engineering with at least 2 years in MLOps on GCP.

Demonstrated success in moving organizations up the MLOps maturity curve.

Experience collaborating with data scientists, data engineers and product managers.

Strong communication skills to translate technical frameworks into business-friendly language.

The Skillset:

Strong hands-on experience with GCP tools such as:

Vertex AI

Big Query

Cloud Storage

Cloud Composer / Airflow

Cloud Build and Cloud Deploy Cloud Functions

MLOps framework and Automation:

Strong understanding of data ingestion pipelines and experiment tracking tools.

Ability to enforce reproducibility and lineage tracking.

Familiarity with Kubeflow and/or TFX

Proven ability to design and implement CI/CD pipeline for ML (automated training, testing, and deployment, integration with Git Hub or Cloud Build)

Experience with model versioning and registry (Vertex AI Model Registry)

Knowledge of Feature Store design.

Ability to setup automated monitoring for data and model drift, model performance.

Experience setting up observability stacks (logging, metrics, alerts, model health dashboards).

Software Engineering and Dev Ops:

Proficiency in Python (mandatory), familiarity with R/Scala/Java as needed.

Experience with containerization (docker) and orchestration (Kubernetes, GKE)
Strong background in infrastructure-as-a-code (Terraform, Deployment Manager)

Ability to implement unit tests, integration tests, and ML-specific validation.

Compliance and Best Practices:

Knowledge of responsible AI practices (bias, explainability)

Familiarity with data governance, security and compliance standards.

Strong ability to document and enforce coding standards, review processes, and reproducibility guidelines.

Nice to have:

Familiarity with the eBook, audiobook, or publishing industry.

Contributions to open-source projects related to MLOps or autonomous systems.

The Perks:

Flexible hours and working environment

4 extended summer long weekends

Full benefits starting from your first day

Paid Volunteer days, unlimited sick days, and 3% RRSP matching

Monthly commuting allowance for hybrid employees

Flexible health spending account

Training budget + Udemy account

Free Kobo device + free weekly e-book or audiobook

Weekly Kobo Tech University sessions

Maternity/paternity leave top up

90 Day Work from Anywhere program

Daily lunch credit when in-office and in-office snacks

Dog friendly office


Increase/decrease your Search Radius (miles)



Job Posting Language