Senior 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 a highly experienced Senior MLOps Developer to spearhead the architecture, optimization, and scaling of the next generation of beauty tech. As a senior member of the team, you will not only build robust systems but also shape our technical strategy and mentor the next generation of engineering talent.This is a 9 Month contract, ending May 31st, 2027.

What You’ll Do

• Architectural Leadership &Industrialization: Architect, design, andindustrializeall stages of the AI/ML pipeline in a cloud environment, encompassing massive-scale data processing, distributed model training, andhighly availableserving.
• 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):Design, provision, and strategically manage cloud-based infrastructure (primarily GCP) usingIaCtools (e.g., Terraform). Implement robust monitoring, logging, and alerting systems to track model drift and infrastructure health in real-time.
• Model Optimization:Lead the optimization of complex deep learning models for seamless, real-time deployment and peak performance across diverse web and mobile platforms.
• LLMDeployment:Drive the industrialization of in-house LLMs by designing highly optimized, GPU-efficient serving architectures.
• Engineering Excellence & Mentorship:Set the gold standard for software development practices. Actively mentor junior and mid-level engineers across both ML and DevOps disciplines, lead peer code reviews, enforce automated testing protocols, and drive continuous architectural improvements.
• Cross-Functional Leadership: Act as a technical bridge and domain expert when industrializing ML models. Work closely with diverse teams to foster a culture of continuous learning, collaboration, and strategic alignment.

What You’ll Need

• Education:Bachelor's or master's degree in computer science, Software Engineering, or a closely related technical field.
• Experience:5+ years of hands-on experience as anMLOpsdeveloper in a cloud-native development environment(DevOps experience is a plus).
• Programming Mastery: A strong software engineering background with exceptional fluency in Pythonand automation languages.
• Containerization & Orchestration: Deepexpertisewith Docker and container orchestration platforms (e.g., Kubernetes), including managing stateful workloads and GPU node pools.
• 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.