Principal Machine Learning Engineer, Content ML, Level 7
About The Position
Snap Inc. is seeking a Principal Machine Learning Engineer to join the Content ML team. This role will focus on building large-scale recommender systems for Snap's video content products. The engineer will lead the vision and roadmap for these systems, enhancing content discovery and personalization across Spotlight, Discover, and Friend Stories. They will technically lead a team of engineers in operating and scaling existing recommender systems, and collaborate with ML, Infra, and Research partners to design next-generation systems incorporating state-of-the-art research in recommendations, foundation models, multimodal understanding, and deep user understanding. The role involves active participation in top-tier conferences and publishing research. The engineer will partner with various stakeholders including product managers, research scientists, data science, and leadership to align on ML strategy and ensure technical investments support company priorities. Responsibilities also include advancing the ML tech stack for recommendations, improving scalability, efficiency, reliability, and performance, staying updated on RecSys trends, and advocating for best practices in availability, scalability, experimentation, operational excellence, and cost management.
Requirements
- 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.
- 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+ years 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 recommendation 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 Snap’s large-scale recommendation systems, elevating content discovery and personalization across Spotlight, Discover, and Friend Stories.
- 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.
- 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.
- 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.
- 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 (equity in the form of RSUs)
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What This Job Offers
Job Type
Full-time
Career Level
Principal
