Principal Machine Learning Engineer, Content ML, Level 7

Vision and Roadmap

We lead the vision and roadmap for Snap’s large-scale recommendation systems, enhancing content discovery and personalization across Spotlight, Discover, and Friend Stories.

Technical Leadership

Technically lead a group of talented engineers from Content ML and Platform teams to operate and scale the existing recommender system. Work with cross-team ML, Infra, and Research partners to design the next-gen recommender system and incorporate SOTA industry research in recommendation systems, foundation models, multimodal signal understanding, deep user understanding, and related areas.

ML Strategy Alignment

Partner with engineers, product managers, research scientists, data science, and leadership to align on ML strategy and ensure technical investments support long-term company priorities.

ML Tech Stack Advancement

Advance the ML tech stack for recommendations, improving scalability, efficiency, reliability, and overall system performance. Stay up to date on emerging trends and advancements in the RecSys landscape and proactively identify opportunities to leverage these developments to further enhance Snap’s content capabilities.

Operational Excellence

Advocate for and implement best practices in availability, scalability, experimentation rigor, operational excellence, and cost management.

Model Development and Deployment

Lead the development and deployment of state-of-the-art machine learning models for performance, reliability, and scale. Quickly learn new technologies and apply them effectively in ambiguous problem spaces.

Collaboration and Mentorship

Skilled at solving complex technical challenges, influencing architecture decisions, and driving execution across multi-stakeholder environments. Strong collaboration, communication, and mentorship abilities.

Qualifications

• Deep understanding of RecSys architectures and experience applying them to real-world production systems.
• Strong foundation in machine learning, deep learning, and large-scale recommendation/ranking systems.
• Experience leading teams or roadmaps focused on recommendations and/or personalization.
• Ability to design, train, deploy, and optimize state-of-the-art machine learning models for performance, reliability, and scale.
• Excellent programming and software engineering skills, with an emphasis on clean design and production-readiness.