Principal Machine Learning Engineer (Generative Recommendations, Level 7)

Requirements

• 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,

• 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,

• (Desirable) Advanced degree in a related field:

• (Desirable) Experience with large-scale recommendation/ranking systems, multimodal modeling, or retrieval architectures,

• (Desirable) Experience with TensorFlow, PyTorch, or related deep learning frameworks,

• (Desirable) Background in integrating generative models into production pipelines,

• (Desirable) Experience partnering with cross-functional executives and management across a globally distributed organization and exercising sound judgment,

• (Desirable) Experience contributing to AI publications

What the job involves

• We’re looking for a Principal Machine Learning Engineer to join the Generative Recommendations for Content products at Snap!,

• 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