Senior Machine Learning Engineer

Rakuten Kobo; Toronto; Hybrid; CAD 100,000 - 130,000; Full time

Job summary

A leading eReading company in Toronto is seeking a Senior ML Engineer to lead the evolution of MLOps capabilities. The role involves transforming manual Machine Learning workflows into an automated framework on Google Cloud Platform. Candidates should have experience in ML Engineering, strong skills in GCP tools, and excellent collaboration abilities. This position offers flexible hours, full benefits, and a supportive work environment.

Benefits

Flexible hours and working environment

4 extended summer long weekends

Full benefits starting from day one

Paid volunteer days and unlimited sick days

Training budget + Udemy account

Dog friendly office

Qualifications

• 5+ years in ML Engineering with 2 years in MLOps on GCP.
• Strong communication skills to translate technical frameworks.
• Demonstrated success in moving organizations up MLOps maturity curve.

Responsibilities

• Collaborate with teams to transform ML workflows to automated framework.
• Streamline ML project lifecycle for continuous business value.
• Design and implement CI/CD pipeline for ML.

Skills

GCP tools

Machine Learning

Python

Containerization

CI/CD pipelines

Data governance

Education

Bachelor's degree in Computer Science or Engineering

Master's degree

Tools

Vertex AI

BigQuery

Cloud Functions

Docker

Kubernetes

Job description

Job Description

Here at Rakuten Kobo Inc. we offer a casual working start‑up environment and a group of friendly and talented individuals. Our employees rank us highly in terms of commitment to work/life balance. We realize that for our people to be innovative, creative and passionate they need to feel valued and supported. We believe in rewarding all our employees with competitive salaries, performance based annual bonuses, stock options.

If you’re looking for a company that inspires passion, personal, and professional growth– join Kobo and come help us make reading lives better.

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
• BigQuery
• 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 GitHub 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 DevOps:

• 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

About Rakuten Kobo Inc.

Owned by Tokyo‑based Rakuten and headquartered in Toronto, Rakuten Kobo Inc. is one of the most advanced global ecommerce companies, with the world’s most innovative eReading services offering more than 6 million eBooks and audiobooks to 30 million + customers in 190 countries. Kobo delivers the best digital reading experience through creative innovation, award‑winning eReaders, and top‑ranking mobile apps. Kobo is a part of the Rakuten group of companies.

Rakuten Kobo Inc. is an equal opportunity employer. Accessibility accommodations for candidates with disabilities participating in the selection process are available on request. Any information received related to accommodation needs of applicants will be addressed confidentially.