Principal Machine Learning Engineer, Content Relevance, Level 7

Snap Inc.•Los Angeles, NC

2d•$235,000 - $414,000•Onsite

About The Position

Snap Inc 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 Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles. Snap Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We’re deeply committed to the well-being of everyone in our global community, which is why our values 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 Content Relevance team Snap! What you’ll do: Drive the technical roadmap of the Content Relevance team and optimize our personalized video recommendation systems Advance the core ML capabilities and design, implement, and scale the overall architecture of the content recommendation systems, ensuring scalability, performance, and reliability Collaborate with cross-functional teams to 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 Collaborate with leadership to up-level the ML tech stack and improve the performance of the organization 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 company

Requirements

Strong understanding of machine learning and deep learning approaches and algorithms, and their applications to advertising, recommendation, and/or search domain
Experience setting the direction for a team whose primary output is online ranking / recommendation models
Ability to design, train, and optimize advanced machine learning models
Excellent programming and software design skills
Ability to proactively learn new concepts and technology and apply them at work
Skilled at solving ambiguous problems and leading and executing complex technical initiatives
Strong collaboration and mentorship skills
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

Nice To Haves

Experience with recommendation systems
Experience with TensorFlow, PyTorch, or related deep learning frameworks
Advanced degree in a related field such as machine learning, computer vision, or mathematics
Experience partnering with cross-functional executives and management across a globally distributed organization and exercising sound judgment
Track record of delivery in rapidly changing, highly collaborative, multi-site, multi-stakeholder environments
Experience working with a diverse group of engineers
Experience contributing to AI publications

Responsibilities

Drive the technical roadmap of the Content Relevance team and optimize our personalized video recommendation systems
Advance the core ML capabilities and design, implement, and scale the overall architecture of the content recommendation systems, ensuring scalability, performance, and reliability
Collaborate with cross-functional teams to 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
Collaborate with leadership to up-level the ML tech stack and improve the performance of the organization
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 company