Principal Machine Learning Engineer, Ad Marketplace, Level 7

is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company’s three core products are , a visual messaging app that enhances your relationships with friends, family, and the world;

, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, . teams build fun and technically sophisticated products that reach hundreds of millions of Snap chatters around the world, every day. We’re deeply committed to the well-being of everyone in our global community, which is why are at the root of everything we do.

We move fast, with precision, and always execute with privacy at the forefront.

We're looking for a Principal Machine Learning Engineer to join the Ad Marketplace team at Snap!

What you’ll do:

* 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.

Knowledge, Skills & Abilities:
* 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.

Minimum Qualifications:

* 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 Qualifications:

* 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 Tensor Flow, PyTorch, or related deep learning frameworks.
* Track record of delivery in rapidly changing, highly collaborative, multi-site, multi-stakeholder environments.
* Experience contributing to AI  you have a disability or special need that requires accommodation, please don’t be shy and provide us some ."Default Together" Policy at Snap:
At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a “default together” approach and expect our team members to work in an office 4+ days per week. At Snap, we believe that having a team of diverse…