Principal Machine Learning Engineer, Generative Recommendations, Level 7

Position Overview

We're looking for a Principal Machine Learning Engineer to join the Generative Recommendations for Content products at Snap. This role will lead the vision and roadmap for generative recommendations by incorporating advanced generative models into Snap's large-scale recommendation systems, elevating content discovery and personalization across Spotlight, Discover and Friend Stories.

Responsibilities

• Lead the vision and roadmap for generative recommendations by incorporating advanced generative models into Snap's large-scale recommendation systems, elevating content discovery and personalization across Spotlight, Discover and Friend Stories.
• Design, build, and scale Generative modeling and build the next generation of the Ranking stack to improve discovery, personalization and user engagement across the platform.
• Develop and apply state-of-the-art multimodal generative models (text, image, video, embeddings) to:
  • Enhance user and content understanding
  • Improve representation learning for content ranking
  • Enable new generative recommendation experiences
• Drive innovation across Snap's content ecosystem by leading high-impact technical initiatives that apply generative AI to improve recommendation quality, personalization, and creator value.
• 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.
• Advance the ML tech stack for recommendations—improving scalability, efficiency, reliability, and overall system performance.
• Keep up-to-date of emerging trends and advancements in the Generative AI landscape and proactively identify opportunities to leverage these developments to further enhance Snap's content capabilities
• Advocate for and implement best practices in availability, scalability, experimentation rigor, operational excellence, and cost management.

Requirements & Skills

Knowledge, Skills & Abilities:

• Deep understanding of generative architectures (e.g., transformers, foundational LLM or VLMs, auto-regressive decoders) 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 recommendation, personalization, or generative AI.
• 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.
• Ability to quickly learn new technologies and apply them effectively in ambiguous problem spaces.
• Skilled at solving complex technical challenges, influencing architecture decisions, and driving execution across multi-stakeholder environments.
• Strong collaboration, communication, and mentorship abilities.

Minimum Qualifications:

• BS in technical field such as computer science, mathematics, statistics or equivalent years of experience
• 9+ years of post-Bachelor's machine learning experience; or a Master's degree in a technical field + 8+ year of post-grad ML experience; or a PhD in a related technical field + 5+ years of post-grad ML experience
• 2+ years of experience with technical leadership or acting as the domain-expert to a technical organization
• Experience developing and shipping performant and scalable machine learning models for recommendation or ranking use cases

Preferred Qualifications:

• Advanced degree in a related field such as machine learning, computer vision, or mathematics
• Experience with large-scale recommendation/ranking systems, multimodal modeling, or retrieval architectures.
• Experience with TensorFlow, PyTorch, or related deep learning frameworks
• Background in integrating generative models into production pipelines
• Experience partnering with cross-functional executives and management across a globally distributed organization and exercising sound judgment
• Experience contributing to AI publications