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Snap Inc. · 1 day ago

Principal Machine Learning Engineer, Generative Recommendations, Level 7

San Francisco, California

Full-time

Onsite

Lead/Staff

$276K/yr - $414K/yr

9+ years exp

Snap Inc. is a technology company focused on improving communication through innovative products. They are seeking a Principal Machine Learning Engineer to lead the vision for generative recommendations, enhancing content discovery and personalization across their platforms.

Computer Software

Comp. & Benefits

H1B Sponsor Likely

Responsibilities

Lead the vision and roadmap for generative recommendations by incorporating advanced generative models into Snap’s large-scale recommendation systems, elevating content discovery and personalization across Spotlight, Discover and Friend Stories

Design, build, and scale Generative modeling and build the next generation of the Ranking stack to improve discovery, personalization and user engagement across the platform

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

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 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

Keep up-to-date of emerging trends and advancements in the Generative AI 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

Qualification

Generative architecturesMachine learningDeep learningRecommendation systemsTensorFlowPyTorchMultimodal modelingTechnical leadershipCollaborationCommunicationMentorship

Required

Deep understanding of generative architectures (e.g., transformers, foundational LLM or VLMs, auto-regressive decoders) 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 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

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

BS in technical field such as computer science, mathematics, statistics or equivalent years of experience

9+ years of post-Bachelor's machine learning experience; or a Master's degree in a technical field + 8+ year 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

Preferred

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 generative models into production pipelines

Experience partnering with cross-functional executives and management across a globally distributed organization and exercising sound judgment

Experience contributing to AI publications

Benefits

Paid parental leave

Comprehensive medical coverage

Emotional and mental health support programs

Compensation packages that let you share in Snap’s long-term success

Company

Snap Inc.

Glassdoor3.6

Snap is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate.

Founded in 2011

Santa Monica, California, US

5001-10000 employees

https://careers.snap.com/

H1B Sponsorship

Snap Inc. has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)

Distribution of Different Job Fields Receiving Sponsorship

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Trends of Total Sponsorships

2025 (394)

2024 (366)

2023 (332)

2022 (356)

2021 (318)

2020 (237)