Machine Learning Developer (AI)

TL;DR

Machine Learning Developer (AI): Build robust, scalable systems that turn AI research into production-ready models for enterprise commerce and self-service use cases with an accent on large-scale training, low-latency inference, and model lifecycle management. Focus on analyzing and improving model performance, deploying and monitoring AI systems, and collaborating with scientists to enhance tools and workflows.

Location: Montreal (Province of Quebec, Canada) - hybrid

Company

Quebec-based pioneer in AI-powered search and recommendations, personalizing digital experiences for customers across websites, e-commerce, contact centers, and intranets.

What you will do

• Contribute to the end-to-end lifecycle of machine learning models, from implementation to testing, deployment, and monitoring.
• Analyze and improve performance of machine learning models and systems for large-scale training and low-latency inference.
• Maintain and enhance client-facing product features powered by machine learning.
• Support adoption of machine learning platforms, observability tools, and best practices for efficiency and reliability.
• Collaborate with peers and scientists to explore new approaches and improve system building and operations.

Requirements

• 2+ years of industry experience working with machine learning systems.
• Hands-on experience deploying, monitoring, and supporting AI models in production.
• Collaborative mindset for working closely with scientists on challenges, tools, and workflows.
• Experience with Python, AWS, Kubernetes, or other relevant technologies.

Nice to have

• Experience in MLOps, machine learning engineering, or large-scale model deployment.
• Experience with data pipelines and structuring data workflows for ML projects.
• Experience contributing to shared internal tools or libraries.
• Knowledge of NLP, information retrieval, or recommendation systems.

Culture & Benefits

• Collaborative, diverse, and trusting environment with talented, passionate people.
• Hybrid work mode with pillar days in Montreal office twice a week for collaboration.
• Modern office infrastructures to enhance cross-team collaboration and well-being.
• Opportunities for continuous learning, new challenges, and skill development.
• Remote options available worldwide with travel for team-building events.