Principal Machine Learning Engineer, Generative Recommendations

Position Overview

Snap Inc. is a technology company that empowers people to express themselves and live in the moment. As a Principal Machine Learning Engineer for Generative Recommendations in Content Products at Snap, you will drive innovation by incorporating advanced generative models into our large-scale recommendation systems and elevate content discovery and personalization across Snapchat’s Spotlight, Discover, and Friend Stories.

Key Responsibilities

• Lead the vision and roadmap for generative recommendations by incorporating advanced generative models into Snap's large-scale recommendation systems.
• Design, build, and scale generative modeling and develop 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, and enable new recommendation experiences.
• Drive innovation by leading high-impact technical initiatives that leverage generative AI to improve recommendation quality and creator value.
• Partner with engineers, product managers, research scientists, data scientists, and leadership to align on ML strategy and long-term company priorities.
• Advance the ML tech stack for recommendations by improving scalability, efficiency, reliability, and overall system performance.
• Keep up-to-date with emerging trends in Generative AI and proactively identify opportunities to enhance Snap's content capabilities.
• Advocate for and implement best practices in system availability, scalability, experimentation rigor, operational excellence, and cost management.

Required Qualifications

• 9+ years of post-Bachelor's machine learning experience; or a Master's degree with 8+ years of post-grad experience; or a PhD with 5+ years of experience.
• 2+ years of experience in technical leadership or acting as a domain expert within a technical organization.
• Deep understanding of generative architectures (e.g., transformers, foundational LLMs/VLMs, auto-regressive decoders) and a strong foundation in machine learning and deep learning.
• Proven experience developing, training, deploying, and optimizing scalable machine learning models for recommendation or ranking use cases.
• 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.
• Strong collaboration, communication, and mentorship abilities; skilled at addressing complex technical challenges and influencing architecture decisions.

Preferred Qualifications

• Advanced degree in machine learning, computer vision, mathematics, or a related field.
• Experience with large-scale recommendation systems, multimodal modeling, or retrieval architectures.
• Proficiency with TensorFlow, PyTorch, or related deep learning frameworks.
• Background in integrating generative models into production pipelines.
• Experience partnering with cross-functional leadership and contributing to AI publications.

Benefits & Perks

• Compensation: Base salary ranges vary by location (Zone A: $276,000-$414,000; Zone B: $262,000-$393,000; Zone C: $235,000-$352,000 annually) and this position is eligible for equity in the form of RSUs. The starting pay is determined by job-related skills, experience, qualifications, work location, and market conditions.
• Paid parental leave and comprehensive medical coverage.
• Emotional and mental health support programs.
• Opportunities to share in Snap's long-term success through competitive compensation packages.