ML Engineering Lead - Ranking & Recommender Systems

Jobtailor; California (MO); On-site; USD 180,000 - 240,000; Full time

Job summary

Snap Inc. seeks a senior leader to head ML and ranking initiatives for Snapchat ads. You will guide a cross-functional team of ML and software engineers, defining architecture, metrics, and a clear product vision to maximize relevance and revenue.

You will champion responsible ML practices, mentor engineers, and drive rapid experimentation with Data Science and Product teams to shape the company’s machine learning strategy.

Qualifications

• Bachelor's in a related technical field such as computer science or equivalent years of experience.
• 8+ years of post-Bachelor’s ML industry experience; or a Master’s degree + 7+ year ML experience; or a PhD + 4+ year ML experience.
• 1+ year leading ML teams focusing on ranking or recommendations.
• Deep understanding of ML approaches and their application to recommender, ads and search systems.
• Experience using large language models for keyword extraction, description generation, and semantic relevance judging.

Responsibilities

• Lead a team of ML and software engineers to build large-scale indexing, retrieval, and ranking systems for Snapchat ads.
• Collaborate with product teams to define architecture and vision for the system and grow the team beyond the initial scope.
• Build the evaluation framework that enables rapid iteration and measurement of outcomes with Data Science and Product partners.
• Develop talent and shape Snap’s broader ML strategy and engineering excellence.

Skills

ML leadership

Communication

Mentorship

Stakeholder collaboration

Problem solving in ambiguity

Deep ML knowledge

Education

Bachelor’s in Computer Science or related field

Master’s degree in technical field

PhD in related technical field

Job description

Snap Inc. seeks a senior leader to head ML and ranking initiatives for Snapchat ads. You will guide a cross-functional team of ML and software engineers, defining architecture, metrics, and a clear product vision to maximize relevance and revenue.

You will champion responsible ML practices, mentor engineers, and drive rapid experimentation with Data Science and Product teams to shape the company’s machine learning strategy.