Principal Machine Learning Engineer, Generative Recommendations, Level 7

Position Overview

Snap Inc is a technology company pioneering in camera innovation, empowering people to express themselves, live in the moment, learn about the world, and have fun together. With flagship products like Snapchat, Lens Studio, and Spectacles, we build fun and sophisticated products that reach hundreds of millions of users every day. We are seeking a Principal Machine Learning Engineer to join the Generative Recommendations for Content products team and drive the integration of advanced generative models into our large-scale recommendation systems.

Key Responsibilities

• Lead the vision and roadmap for generative recommendations by incorporating advanced generative models into Snap’s large-scale recommendation systems to elevate content discovery and personalization across Spotlight, Discover, and Friend Stories.
• Design, build, and scale generative modeling systems and the next generation of the ranking stack to improve discovery, personalization, and user engagement.
• 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, and 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 scientists, and leadership to align on machine learning strategy and ensure technical investments support long-term company priorities.
• Advance the ML tech stack to improve scalability, efficiency, reliability, and overall system performance.
• Stay current with emerging trends in generative AI and proactively identify opportunities to enhance Snap’s content capabilities.
• Advocate for and implement best practices in availability, scalability, experimentation rigor, operational excellence, and cost management.

Required Qualifications

• Deep understanding of generative architectures (e.g., transformers, foundational LLMs/VLMs, auto-regressive decoders) with proven experience in applying them to 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.
• Demonstrated ability to quickly learn and apply new technologies in ambiguous problem spaces.
• Skilled at solving complex technical challenges, influencing architecture decisions, and driving execution across multi-stakeholder environments.
• Education: BS in a technical field such as computer science, mathematics, or statistics, or equivalent experience.
• Experience Required: 9+ years of post-Bachelor's machine learning experience; or a Master's degree with 8+ years of experience; or a PhD with 5+ years of experience, including at least 2+ years in technical leadership or acting as a domain expert.
• Proven experience in developing and shipping performant and scalable machine learning models for recommendation or ranking use cases.

Preferred Qualifications

• 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.
• Proficiency with deep learning frameworks such as TensorFlow or PyTorch.
• Background in integrating generative models into production pipelines.
• Experience partnering with cross-functional executives and management in a globally distributed organization.
• Experience contributing to AI publications.

Benefits & Perks

• Benefits: Paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages designed to share in Snap’s long-term success.
• Compensation: In the United States, work locations are assigned a pay zone:
  Zone A (CA, WA, NYC): $276,000-$414,000 annually; Zone B: $262,000-$393,000 annually; Zone C: $235,000-$352,000 annually. This position is also eligible for equity in the form of RSUs.