Principal Machine Learning Engineer, Generative Recommendations

Snap Inc.Los Angeles, NC
4d$235,000 - $414,000Onsite

About The Position

Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company’s three core products are Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles. We’re looking for a Principal Machine Learning Engineer to join the Generative Recommendations for Content products at Snap! What you’ll do 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

  • 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.
  • 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

Nice To Haves

  • 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

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.

Benefits

  • paid parental leave
  • comprehensive medical coverage
  • emotional and mental health support programs
  • compensation packages that let you share in Snap’s long-term success!

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What This Job Offers

Job Type

Full-time

Career Level

Principal

Education Level

Ph.D. or professional degree

Number of Employees

1,001-5,000 employees

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