Staff Machine Learning Engineer (Ad Ranking)

TL;DR

Staff Machine Learning Engineer (Ad Ranking): Designing, building, and deploying machine learning solutions for Snap's ad optimization stack with an accent on driving technical direction and advancing core ML capabilities. Focus on owning outcomes for large, cross-team ML initiatives, establishing technical vision, and resolving complex technical tradeoffs.

Location: This is an onsite position based in the United States, requiring work in the office 4+ days per week in one of the following locations: Bellevue, New York, Palo Alto, San Francisco, Santa Monica, or Seattle.

Salary: $195,000–$343,000 annually

Company

Snap Inc is a technology company that empowers people to express themselves, live in the moment, learn about the world, and have fun together through products like hirify.global, Lens Studio, and Spectacles.

What you will do

• Set and drive the technical direction for the Ad Ranking team and advance core ML capabilities.
• Design, build, and deploy machine learning solutions to support Snap's monetization strategies.
• Own outcomes for large, cross-team ML initiatives from problem definition through long-term impact.
• Establish technical vision and roadmaps, and resolve complex technical tradeoffs across teams.
• Influence and mentor engineers across organizational boundaries through technical leadership.

Requirements

• 8+ years of post-Bachelor’s machine learning experience (or Master’s + 7+ years; or PhD + 4 years).
• Strong understanding of machine learning and deep learning approaches and algorithms, especially in advertising, recommendation, or search domains.
• Experience developing machine learning models for ranking, recommendations, search, or advertising.
• Ability to design, train, and optimize advanced machine learning models.
• Skilled at solving open ambiguous problems and proactively learning new concepts.
• Strong collaboration and mentorship skills.

Nice to have

• Experience in online advertising, including ad targeting, ranking, auction, and/or marketplace optimization.
• Advanced degree in computer science or related field.
• Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, or scikit-learn.
• Experience working with machine learning, ranking infrastructures, and system design.

Culture & Benefits

• Practice a “default together” approach, requiring team members to work in an office 4+ days per week.
• Comprehensive benefits package includes paid parental leave, medical coverage, and mental health support.
• Compensation packages allow for sharing in Snap’s long-term success through equity in the form of RSUs.
• Committed to a diverse and inclusive environment as an equal opportunity employer.