Applied Researcher 3

About the role

Work arrangement

• Hybrid role requiring presence in the Toronto office three days per week.

What you will do

• Develop and deploy visual and multimodal models for recognition, visual understanding, content intelligence, retrieval, and decisioning.
• Design and optimize production training and inference pipelines, including orchestration of models and services.
• Advance detection, segmentation, classification, metric and contrastive learning, and visual-language modeling capabilities.
• Lead research initiatives, adapt foundation models, and develop specialized architectures, data strategies, training methods, and evaluation approaches.
• Lead work on visual-language model training and fine-tuning, model distillation, reinforcement learning, and other modern AI methods.
• Partner with product, engineering, design, and applied science colleagues to turn business opportunities into technical roadmaps and delivered solutions.
• Communicate technical direction and trade-offs to stakeholders, and mentor researchers and other team members.

Qualifications

• Ph.D. or M.S. in Computer Science, Electrical Engineering, Machine Learning, Applied Mathematics, or a related technical field focused on computer vision, multimodal AI, or artificial intelligence.
• At least three years of experience building computer vision and/or multimodal systems for large-scale applications.
• Experience taking machine learning solutions from research through production, including training, evaluation, and inference pipelines and model integration.
• The role calls for leadership of ambiguous research problems, stakeholder communication, and mentoring.