Manager, ML/AI Engineer, Data & AI

Job description

Responsibilities

• Work with client teams to identify business problems that AI and advanced analytics can solve.
• Translate client goals into complete ML/AI solution architectures, from data through deployment.
• Explore and prepare data and build models for forecasting, recommendations, classification, and anomaly detection.
• Design and refine generative-AI solutions on Azure, Google Cloud, and AWS AI platforms.
• Set up production ML pipelines with automated testing, version control, continuous deployment, and monitoring.
• Track model performance, identify drift, and plan retraining after launch.
• Work with data engineers to establish dependable, scalable data foundations for training and inference.
• Embed fairness, transparency, governance, and privacy safeguards in solutions.
• Lead and contribute to client workshops and presentations about AI strategy and implementation.

Requirements

• Degree in computer science, engineering, data science, mathematics, or a similar field.
• At least 5 years in machine learning, data science, or AI engineering, including production ML delivery.
• Advanced Python for analysis, modeling, and engineering.
• Hands-on experience with libraries or platforms such as PyTorch, TensorFlow, scikit-learn, Databricks, or Azure ML.
• Strong grounding in statistics, ML algorithms, feature engineering, and model evaluation.
• Experience building ML pipelines across preprocessing, training, validation, deployment, and monitoring.
• Working knowledge of MLOps, including experiment tracking, model versioning, CI/CD, and automated retraining.
• Experience deploying on Azure, AWS, or GCP and understanding cloud architecture and security.
• Direct LLM and generative-AI experience, such as prompt engineering or RAG.
• Client-facing confidence, clear communication to business audiences, and cross-disciplinary collaboration.

Preferred qualifications

• Spark or other distributed processing experience is a plus.
• Foundation-model fine-tuning is an asset.
• A cloud AI or ML certification from Azure, AWS, Google Cloud, or Databricks is a plus.

Compensation and benefits

• Base salary is CAD 101,000 to CAD 135,000, depending on location, skills, and experience; annual bonus awards may also be available.
• The role includes a full benefits package with health and wellness coverage.

Role highlights