Machine Learning Engineer II, Ads

Responsibilities

• Design, develop, and deploy machine learning solutions involving data pipelines, model architectures, and serving integrations for advertising systems.
• Formulate ambiguous modeling problems and translate business observations into ML research directions with clear evaluation criteria.
• Collaborate with product managers, data scientists, and infrastructure engineers to develop impactful ML applications.
• Refine and advance algorithms and models to improve operational efficiency and advertising outcomes.
• Publish and present findings internally and contribute to design reviews, paper sharing, and experiment retrospectives.

Requirements

• Graduate degree (master’s or PhD) in machine learning, statistics, computer science, information retrieval, or a closely related quantitative field.
• Strong programming skills and fluency in SQL, Spark, Pandas, classical machine learning, and deep learning tools.
• Strong analytical and problem-solving skills.
• Strong communication and collaboration skills across diverse stakeholders.
• Preferred: 1–2 years of industry experience applying machine learning to real-world problems with large datasets.
• Preferred: knowledge of sequential modeling, Transformer architecture, and foundation models.
• Preferred: familiarity with LLM integrations, agentic workflows, and productivity tooling.
• Preferred: experience building large-scale online recommendation systems.

Benefits

• Remote Flex First work arrangement, with flexibility to work from home, an office, or another preferred location.
• Eligible for a new-hire equity grant and annual refresh grants.
• Hiring is currently limited to Ontario, Alberta, British Columbia, and Nova Scotia for Canadian candidates.
• Base pay range is CAD 154,000–162,500, excluding equity and other compensation.