MLOps Developer

MLOps Developer

Research, innovation, and scale! ModiFace is the first tech company to be acquired by beauty giant L’Oréal and provides industry leading AR and AI technology to the most influential brands in the world. ModiFace’s patented technology is based on more than a decade of advanced facial recognition research at the University of Toronto and in collaboration with L'Oréal’s Research and Innovation team. 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 andmaintainContinuous Integration and Continuous Deployment pipelines specifically tailored for ML artifacts (data, models, and code)
• Infrastructure as Code ( IaC ) : Work with DevOps team to provision, manage, and scale cloud-based infrastructure (primarily GCP) to support high-throughput inference
• Model Optimization : Optimizedeep 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 activelyparticipatingin 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 : Deepexpertisewith 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 : Demonstratedsuccess 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 ModiFace , we believe compensation should be transparent, fair, and reflective of both experience and impact. The total compensation range for this role is $145,000 - 155,000/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 ModiFace , 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 ModiFace , 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.