TL;DR

Principal Machine Learning Engineer (AI): Leading the vision and roadmap for generative recommendations by incorporating advanced generative models into Snap’s large-scale recommendation systems, elevating content discovery and personalization. Focus on designing, building, and scaling generative modeling and the next generation of the ranking stack to improve discovery, personalization, and user engagement across the platform.

Location: Onsite in Bellevue, Los Angeles, Palo Alto, San Francisco, or Seattle, US. Must work in office 4+ days per week.

Salary: $235,000–$414,000 annually

Company

Snap Inc is a technology company focused on improving communication through camera-based products like %hirify_global%, Lens Studio, and Spectacles.

What you will do

Lead the vision and roadmap for generative recommendations by incorporating advanced generative models into large-scale recommendation systems.
Design, build, and scale generative modeling and the next generation of the ranking stack.
Develop and apply state-of-the-art multimodal generative models to enhance user and content understanding and improve representation learning.
Drive innovation by leading high-impact technical initiatives applying generative AI to improve recommendation quality and personalization.
Partner with cross-functional teams to align on ML strategy and ensure technical investments.
Advance the ML tech stack for recommendations, improving scalability, efficiency, and reliability.

Requirements

9+ years of post-Bachelor’s machine learning experience (or 8+ with Master's, 5+ with PhD).
2+ years of technical leadership or acting as a domain expert.
Experience developing and shipping performant and scalable machine learning models for recommendation or ranking use cases.
Deep understanding of generative architectures (e.g., transformers, foundational LLM or VLMs, auto-regressive decoders).
Strong foundation in machine learning, deep learning, and large-scale recommendation/ranking systems.
Excellent programming and software engineering skills for production-readiness.

Nice to have

Advanced degree in 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 contributing to AI publications.

Culture & Benefits

"Default Together" policy requiring 4+ days per week in office.
Comprehensive benefits including paid parental leave, medical coverage, and emotional/mental health support programs.
Compensation packages include equity in the form of RSUs.
Commitment to diversity and inclusion.
Opportunities to work on innovative AR & VR technologies.