Principal Machine Learning Engineer, Content ML, Level 7

We're looking for a Principal Machine Learning Engineer to join the Content ML team at Snap! We build large-scale recommender systems for all of Snap's video content products.

- 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. We actively participate in and publish at top-tier conferences.

- 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.

- 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

- 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

Zone A (CA, WA, NYC) : The base salary range for this position is $276,000-$414,000 annually.

Zone B : The base salary range for this position is $262,000-$393,000 annually.

Zone C : The base salary range for this position is $235,000-$352,000 annually.