Senior MLOps Engineer — Cloud AI for Beauty Tech

L'Oréal; Toronto; On-site; CAD 145,000 - 155,000; Full time

Benefits offered by this job

Health & dental benefits

Profit sharing

RRSP matching

Employee assistance programs

Team lunches

Job summary

ModiFace, a L’Oréal company, is seeking an experienced MLOps developer to scale next‑generation beauty tech. You will automate AI/ML pipelines, build ML-focused CI/CD, and provision scalable GCP infrastructure for high-throughput inference.

You’ll collaborate with ML engineers and product teams to deploy optimized models and integrate LLM-enabled features in a fast-paced Agile environment. Competitive compensation and benefits accompany this role.

Qualifications

• Bachelor's or Master's in CS/SE.
• 3+ years as an MLOps developer in a cloud-native environment.
• Strong Python programming skills.
• Deep expertise with Docker and Kubernetes.
• Extensive hands-on experience provisioning and managing GCP infrastructure.
• Solid knowledge of ML frameworks and lifecycle tools (MLflow, DVC).
• Experience working in Agile/SCRUM.
• Excellent communication for non-technical audiences.

Responsibilities

• End-to-End Automation: build automated tools across the AI/ML pipeline in cloud environments.
• CI/CD for ML artifacts: design and maintain pipelines for data, models, and code.
• IaC: provision and scale cloud infrastructure (GCP) to support high-throughput inference.
• Model optimization for deployment on web and mobile.
• LLM integration: convert domain APIs into structured, controllable tools.
• Foster software engineering best practices through code reviews, testing, and agile ceremonies.
• Collaborate cross-functionally to industrialize ML models and promote continuous learning.

Skills

MLOps

Python

Docker

Kubernetes

GCP

MLflow

DVC

Agile/SCRUM

Education

Bachelor's or Master's in CS/SE

Tools

MLflow

DVC

Job description

ModiFace, a L’Oréal company, is seeking an experienced MLOps developer to scale next‑generation beauty tech. You will automate AI/ML pipelines, build ML-focused CI/CD, and provision scalable GCP infrastructure for high-throughput inference.

You’ll collaborate with ML engineers and product teams to deploy optimized models and integrate LLM-enabled features in a fast-paced Agile environment. Competitive compensation and benefits accompany this role.