Manager, ML/AI Engineer, Data & AI in Toronto

Toast is recruiting on behalf of a global professional services firm with more than 10,000 people across Canada, serving many of the country’s largest enterprises and public sector organizations. Its AI team helps clients take machine learning and generative AI from proof of concept to secure, scalable production. They are hiring a Manager, ML/AI Engineer to work directly with clients, architect AI solutions end to end, and get them running reliably in the cloud and on-prem. This is a full-time, hands-on role based in Toronto, Vancouver, or Calgary.

Responsibilities

• Work alongside client teams to pinpoint business problems that AI and advanced analytics can solve.
• Turn client goals into complete ML/AI solution architectures, from data to deployment.
• Build models for real business needs like demand forecasting, recommendations, classification, and spotting anomalies, starting with data exploration and preparation.
• Design and refine generative AI solutions on leading cloud AI platforms across Azure, Google Cloud, and AWS.
• Set up production-grade ML pipelines with automated testing, version control, continuous deployment, and monitoring.
• Keep models healthy after launch by tracking performance, catching drift, and planning retraining.
• Team up with data engineers so training and inference run on dependable, scalable data foundations.
• Build fairness, transparency, governance, and privacy safeguards into every solution.
• Lead and contribute to client workshops and presentations on AI strategy and implementation.

Requirements

• Degree in computer science, engineering, data science, math, or a similar field.
• 5+ years in machine learning, data science, or AI engineering, including shipping ML solutions to production.
• Advanced Python for analysis, modelling, and engineering work.
• Hands-on experience with popular ML libraries and platforms such as PyTorch, TensorFlow, scikit-learn, Databricks, or Azure ML.
• Strong foundation in statistics, ML algorithms, feature engineering, and model evaluation.
• Track record building full ML pipelines covering preprocessing, training, validation, deployment, and monitoring.
• Working knowledge of MLOps, including experiment tracking, model versioning, CI/CD, and automated retraining.
• Experience deploying models on Azure, AWS, or GCP, with a solid understanding of cloud architecture and security.
• Direct experience with LLMs and generative AI, such as prompt engineering or RAG.
• Client-facing confidence and the ability to make technical ideas clear to business audiences.
• Comfortable working across disciplines to solve complex problems as a team.

Nice to Haves

• Experience with Spark or other distributed processing tools would be a plus.
• Experience fine-tuning foundation models is considered an asset.
• A cloud AI or ML certification from Azure, AWS, Google Cloud, or Databricks would be a plus.

Benefits

• Base salary of $101,000 to $135,000, depending on location, skills, and experience.
• Eligibility for annual bonus awards on top of base salary.
• Full benefits package, including health and wellness coverage.
• Choice of three major Canadian tech hubs: Toronto, Vancouver, or Calgary.
• Build production AI systems that large Canadian organizations rely on to make decisions every day, from forecasting demand to flagging anomalies before they become costly problems.
• Shape how major organizations adopt AI responsibly, embedding explainability, bias detection, and governance into the systems you deliver.
• Hands-on exposure to all three major clouds and the latest GenAI tooling, building a skill set that stays in high demand.
• A manager-level seat with direct client access, giving you a strong runway toward senior leadership in AI consulting.