Principal Machine Learning Engineer, Signals and Measurement

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 operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services.

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 our Signals & Measurement team at Snap!

What you’ll do:

• Design and develop machine learning systems across the third-party signal lifecycle, from acquisition and curation to matching, attribution, and causal measurement
• Design, implement, and scale critical machine learning models to support Snap's monetization strategies
• 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
• 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 ML community

Knowledge, Skills & Abilities:

• Strong understanding of machine learning and deep learning approaches and algorithms, and their applications to advertising measurement, 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

Minimum Qualifications:

• Bachelor's in a 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
• Experience with TensorFlow, PyTorch, or related deep learning frameworks

Preferred Qualifications:

• Experience with signals and measurement stack, identity resolution, anomaly detection or causal measurement
• Familiar with attribution and advanced measurement methodologies
• Experience in online advertising, including ad targeting, ranking, auction, and/or marketplace optimization.
• 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

"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 backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.

We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable).

Our Benefits: Snap Inc. is its own community, so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap’s long-term success!

Compensation

In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future.

Zone A (CA, WA, NYC):

Zone B:

Zone C:

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