Staff ML Research Engineer
On-siteToronto, Ontario, Canada
Job Summary
Design and implement advanced artificial intelligence systems and architectures to address complex organizational challenges, while leading cross-functional collaboration with internal teams and external academic research groups. Drive the evaluation and adoption of new technologies and methodologies to optimize performance and deliver measurable business value. Oversee decision-making for highly complex issues with significant financial or operational impact, providing strategic direction to management. Mentor junior developers and teams to foster skill development and ensure the successful execution of high-impact projects. Cultivate high-impact relationships across multiple areas to provide strategic insights as a trusted advisor. This role supports the AI Group's mission to scale early-stage AI projects into client outcomes and advance research into generative and agentic AI.
Required Qualifications
- Ph.D. degree in Computer Science, Statistics, Machine Learning, or a related technical field
- 10+ years of experience leading high-impact machine learning solutions in a product-centric environment
- Experience managing/mentoring high-performing teams of researchers, data scientists, and engineers
- Proven expertise across the research and development lifecycle, from prototyping to production, with strong ability to engage stakeholders
- Deep expertise in machine learning, statistics, and data science with experience in optimization, A/B testing, and causal inference
- Exceptional communication skills and ability to translate complex concepts to diverse audiences
- Demonstrated a mastery of end-to-end ML system ownership in production environments, including model design, feature engineering, model architecture, drift detection, and serving infrastructure at scale
- A deep expertise in building models that serve as shared ML platforms for multiple downstream teams and use cases
- A proven ability to lead cross-functional technical initiatives by coordinating with diverse stakeholder groups (feature providers, policy teams, client teams) while maintaining system integrity and translating technical results to non-technical audiences
- Demonstrated a strong track record of leading and mentoring senior engineers through career advancement and establishing thought leadership as the primary technical authority on complex, mission-critical systems
- Experience transferring ML expertise across domains and applying behavioral signal analysis, anomaly detection, or graph-based systems to high-stakes production environments with real-world business impact
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