Staff Machine Learning Engineer, Shopping Merchants

About the role

You will serve as the first dedicated machine learning engineering hire for the Merchant team, shaping the technical roadmap for merchant presence and shopping discovery. This role focuses on building and scaling LLM-driven systems to improve merchant quality, brand affinity, and overall user trust across the platform.

Key facts

What you'll do

• Lead the end-to-end technical strategy, architecture, and execution for machine learning initiatives, moving from initial prototypes to production-grade systems.
• Design and deploy GenAI and LLM-based applications for entity resolution, content enrichment, attribute extraction, and merchant quality signaling.
• Develop rigorous evaluation frameworks, including automated regression testing, human-in-the-loop review processes, and offline-to-online metric alignment.
• Partner with product, data science, and platform teams to translate complex business requirements into actionable ML deliverables.
• Establish engineering standards for the organization, including monitoring, alerting, and launch readiness protocols.
• Mentor team members and support future hiring efforts to scale the machine learning engineering function.

Requirements

• 8+ years of professional experience in software engineering, applied ML, or ML engineering, with significant time spent at a Staff-level IC capacity.
• Proven history of leading 0-to-1 ML or LLM projects that resulted in measurable production impact.
• Hands-on experience building and maintaining LLM-powered applications in production, with a focus on reliability, latency, and safety guardrails.
• Expertise in domains such as ranking, recommendation, retrieval, commerce, or content understanding.
• Strong systems design skills with the ability to balance trade-offs in scalability, cost, and performance.
• Bachelor degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.

Skills & tools

• LLM and GenAI application development
• Machine learning systems design
• Evaluation and measurement strategy (A/B testing, golden datasets)
• Production-scale ML operations

Practical notes

• This role requires working from the Toronto office 1 day per week.
• Relocation assistance is not provided for this position.
• Final compensation is determined based on factors including experience, skills, and expertise.