Machine Learning Engineer, Revenue+

Snap is seeking a founding Machine Learning Engineer for the Revenue+ team in New York, NY. This role will establish machine learning as a core capability to support subscription growth and monetization across Snapchat+ subscriptions, with end-to-end responsibility from problem framing through production and measurement.

Key Responsibilities

• Locate high-impact opportunities where machine learning can improve subscription growth, monetization, retention, and subscriber value
• Design, build, and deploy machine learning systems for personalization, ranking, propensity modeling, offer decisioning, and lifecycle optimization
• Drive the complete workflow from ambiguous business needs and data exploration to experimentation, production deployment, measurement, and iterative improvement
• Set technical direction and establish best practices for a new Revenue+ machine learning capability
• Collaborate closely with Product, Data Science, Backend Engineering, and Mobile Engineering to shape product strategy and prioritize machine learning investments
• Develop production-grade machine learning systems that are reliable, observable, and scalable for serving Snapchatters at significant scale
• Use AI tools to design and ship scalable services while maintaining rigorous standards for code correctness, security, and production readiness

Required Qualifications

• Strong understanding of machine learning and software engineering fundamentals
• Strong product and business judgment, including the ability to identify where machine learning can deliver measurable incremental value
• Experience with ranking, recommendation, personalization, propensity modeling, decisioning, or related product machine learning systems
• Ability to translate ambiguous business challenges into concrete machine learning opportunities and technical plans
• Ability to work with substantial autonomy and take end-to-end technical ownership
• Strong collaboration and mentorship skills
• Proficiency in, or strong aptitude for, leveraging AI tools to streamline development, plus the judgment to audit outputs for architectural integrity, performance bottlenecks, and security risks
• Bachelor’s Degree in a relevant technical field such as computer science, or equivalent years of practical work experience
• 5+ years of post-Bachelor’s machine learning experience, or Master’s degree in a technical field plus 4+ years of post-grad machine learning experience, or PhD in a relevant technical field plus 1 year of post-grad machine learning experience
• Experience developing and productionizing machine learning systems for ranking, recommendation, personalization, propensity modeling, decisioning, monetization, retention, or other relevant product machine learning applications
• Experience taking machine learning systems from ambiguous problem statements through experimentation and into production

Benefits

• Paid parental leave
• Comprehensive medical coverage
• Emotional and mental health support programs
• Compensation packages

Preferred Qualifications

• Advanced degree in computer science or a related field
• Experience with subscription, monetization, pricing, offers, retention, or lifecycle optimization
• Experience collaborating extensively with Backend and Mobile Software Engineers
• Experience with causal inference, uplift modeling, experimentation, customer lifetime value, or incremental impact measurement
• Experience optimizing machine learning systems against business or revenue outcomes
• Experience operating production machine learning systems at significant scale
• Experience as an early or founding machine learning engineer, or in an environment requiring broad technical and product ownership

Work Location and Schedule

DEFAULT TOGETHER POLICY AT SNAP: Expect team members to work in an office 4+ days per week.

Compensation

• Zone A (CA, WA, NYC): $209,000 to $313,000 base salary annually
• Zone B: $199,000 to $297,000 base salary annually
• Zone C: $178,000 to $266,000 base salary annually

This position is eligible for equity in the form of RSUs.