More jobs:
MLOps Developer
Job in
Toronto, Ontario, C6A, Canada
Listed on 2026-06-22
Listing for:
L'Oréal
Full Time
position Listed on 2026-06-22
Job specializations:
-
Software Development
Machine Learning/ ML Engineer, AI Engineer (Applied/Software), DevOps, Cloud Engineer - Software
Job Description & How to Apply Below
Our services include live 3D makeup and skin care simulation, anti‑aging/skin‑care diagnostics, and live hair colour simulation.
The Role In this critical role, you will work with bright and insightful minds, passionate professionals, and a welcoming community where your creative ideas are exceedingly valued. We are seeking an experienced MLOps developer, helping us scale the next generation of beauty tech.
What You’ll Do
End-to-End Automation:
Develop automated tools for all stages of the AI/ML pipeline in a cloud environment, spanning data processing, model training, and serving
CI/CD for Machine Learning:
Design and maintain Continuous Integration and Continuous Deployment pipelines specifically tailored for ML artifacts (data, models, and code)
Infrastructure as Code (IaC):
Work with Dev Ops team to provision, manage, and scale cloud-based infrastructure (primarily GCP) to support high‑throughput inference
Model Optimization:
Optimize deep learning models for seamless deployment and performance across web and mobile platforms.
LLM Integration:
Collaborate closely with ML engineers and product teams to convert domain‑specific APIs into structured, LLM‑controllable tools.
Engineering Excellence:
Champion best software development practices by actively participating in peer code reviews, automated testing, and agile ceremonies.
Cross‑Functional
Collaboration:
Industrialize ML models by working closely with diverse teams, fostering a culture of continuous learning, collaboration, and improvement.
What You’ll Need
Education:
Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a closely related technical field.
Experience:
3+ years of hands‑on experience as an MLOps developer in a cloud‑native development environment.
Programming Mastery: A strong software engineering background with exceptional fluency in Python.
Containerization & Orchestration:
Deep expertise with Docker and container orchestration platforms (e.g., Kubernetes).
Cloud Platforms:
Extensive, hands‑on experience provisioning and managing infrastructure on cloud providers (GCP is strongly preferred).
ML Ecosystem:
Solid practical knowledge of ML frameworks and lifecycle tracking tools (e.g., MLflow, DVC).
Agile Mindset:
Demonstrated success working in a fast‑paced Agile/SCRUM development setting.
Exceptional Communication:
The aptitude to translate complex mathematical and scientific concepts into clear, understandable terms for non‑technical audiences, coupled with a passion for global teamwork.
Compensation
At Modi Face, we believe compensation should be transparent, fair, and reflective of both experience and impact. The total compensation range for this role is $145,/year, and is determined based on skills, experience, and the scope and complexity of the role. We value open conversations about compensation and are happy to discuss our approach at any stage of the hiring process.
What We Offer
When you join Modi Face, you’ll enjoy working with a team of passionate software developers and business professionals who are open and collaborative within an inclusive environment. We offer an opportunity to advance and refine your skills and talent.
Along with a competitive salary, we offer access to Health & Dental Benefits, including company‑sponsored Wellness & Training programs, Profit Sharing, RRSP Matching, Employee Assistance Programs, exciting in‑office and off‑site social activities, team lunches, a stocked kitchen, and more!
At Modi Face, we create software used by diverse people globally. We value diversity and inclusion within our team to ensure we can deliver the most fair and accessible technology possible, so we welcome and encourage all persons to apply. Accommodations are available upon request for candidates taking part in all aspects of the selection process.
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