Principal Machine Learning Engineer (Content ML)

TL;DR

Principal Machine Learning Engineer (Content ML): Building and scaling large-scale recommender systems for Snap's video content products with an accent on personalization and content discovery. Focus on designing next-gen recommendation architectures, integrating foundation models, and enhancing multimodal signal understanding.

Location: Must be based in the US (Bellevue, Los Angeles, New York, Palo Alto, San Francisco, or Seattle). Office attendance required 4+ days per week.

Salary: $235,000 – $414,000 per year + RSUs

Company

Technology company specializing in visual communication, augmented reality, and the Snapchat ecosystem.

What you will do

• Lead the vision and roadmap for large-scale recommendation systems across Spotlight, Discover, and Friend Stories.
• Technically lead cross-functional engineers from Content ML and Platform teams to scale existing systems.
• Design next-gen recommender systems using SOTA research, foundation models, and multimodal signal understanding.
• Partner with PMs, research scientists, and leadership to align ML strategy with company priorities.
• Advance the ML tech stack to improve scalability, efficiency, and system performance.
• Implement best practices for availability, experimentation rigor, and operational excellence.

Requirements

• 9+ years of ML experience (post-Bachelor's) or equivalent with advanced degrees (Master's + 8 years or PhD + 5 years).
• 2+ years of experience in technical leadership or as a domain expert for a technical organization.
• Proven track record of shipping performant and scalable ML models for recommendation or ranking use cases.
• Deep understanding of RecSys architectures and deep learning foundations.
• Strong software engineering skills with an emphasis on clean design and production-readiness.
• Must be based in one of the specified US office locations.

Nice to have

• Advanced degree in Machine Learning, Computer Vision, or Mathematics.
• Experience with TensorFlow, PyTorch, or similar deep learning frameworks.
• Experience with multimodal modeling or retrieval architectures.
• Contributions to AI publications.

Culture & Benefits

• Comprehensive medical coverage and emotional/mental health support programs.
• Paid parental leave.
• Compensation packages including equity (RSUs).
• Collaborative "Default Together" environment emphasizing in-person teamwork.