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Snap Inc. · 21 hours ago

Principal Machine Learning Engineer, Ad Marketplace, Level 7

Palo Alto, CA

Full-time

Onsite

Lead/Staff

$276K/yr - $414K/yr

9+ years exp

Snap Inc is a technology company that believes in the power of the camera to improve communication and human progress. They are seeking a Principal Machine Learning Engineer to drive the technical roadmap of their Ad Marketplace, design and scale machine learning models, and collaborate with cross-functional teams to enhance advertising efficiency.

Computer Software

Comp. & Benefits

H1B Sponsor Likely

Responsibilities

Drive the technical roadmap of our Ad Marketplace and Pacing teams, advancing the sophistication of our systems, optimize ad spend and delivery, and make our auction more efficient

Design, implement, and scale machine learning models and control systems to efficiently and optimally run our ad marketplace

Collaborate with cross-functional teams to set and align on machine learning strategies to meet company objectives

Stay up-to-date with the latest technology in machine learning and apply this knowledge to tackle complex problems in innovative ways

Work across teams to understand product requirements, evaluate trade-offs, and deliver the solutions needed to build innovative products or services

Advocate for and apply best practices when it comes to availability, scalability, operational excellence, and cost management

Provide technical direction that influences the entire ML community

Qualification

Machine LearningDeep LearningTechnical LeadershipTensorFlowPyTorchSoftware EngineeringCollaborationCommunicationMentorship

Required

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

Strong understanding of machine learning and deep learning approaches and algorithms, and their applications to advertising, recommendation, and/or search domain

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 ambiguous problems and leading and executing complex technical initiatives

Strong collaboration, communication, and mentorship abilities

Preferred

Advanced degree in a related field such as machine learning, computer vision, or mathematics

Experience in online advertising (including ad ranking, auction, marketplace optimization) or other online two-sided markets (e.g., job markets and matching)

Experience with TensorFlow, PyTorch, or related deep learning frameworks

Track record of delivery in rapidly changing, highly collaborative, multi-site, multi-stakeholder environments

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

Represents job field similar to this job

Trends of Total Sponsorships

2025 (394)

2024 (366)

2023 (332)

2022 (356)

2021 (318)

2020 (237)