Machine Learning Engineer, Revenue+

Snap is hiring a founding Machine Learning Engineer for the Revenue+ team to build machine learning as a core capability for subscription growth and monetization across Snapchat+.

Responsibilities

• Spot high-value use cases where machine learning can improve subscription growth, monetization, retention, and subscriber value
• Design, build, and deploy ML systems for personalization, ranking, propensity modeling, offer decisioning, and lifecycle optimization
• Drive end-to-end ownership: turn ambiguous business needs into data exploration, experiments, production deployment, measurement, and iteration
• Set technical direction and establish best practices for a new Revenue+ ML capability
• Collaborate with Product, Data Science, Backend, and Mobile Engineering to shape product strategy and prioritize ML investments
• Build production ML systems that are reliable, observable, and scalable at meaningful service volume for Snapchatters
• Use AI tools to accelerate development and delivery while maintaining rigorous standards for code correctness, security, and production quality

Requirements

• Strong foundation in machine learning and software engineering
• Strong product and business judgment to identify where ML can deliver measurable incremental value
• Experience with ranking, recommendation, personalization, propensity modeling, decisioning, or closely related product ML systems
• Ability to independently translate ambiguous business problems into concrete ML opportunities and technical plans
• Capability to operate with substantial autonomy and take end-to-end technical ownership
• Strong collaboration and mentorship skills
• Proficiency in leveraging AI tools to streamline development, with critical 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 + 4+ years post-grad ML experience, or PhD + 1 year post-grad ML experience
• Experience developing and productionizing ML systems for ranking, recommendation, personalization, propensity modeling, decisioning, monetization, retention, or other relevant product ML applications
• Experience taking ML systems from ambiguous problem statements through experimentation into production

Preferred Qualifications

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

Benefits

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

Work Location and Policy

• Location: New York, NY (onsite)
• Office expectation: work in an office 4+ days per week

Compensation

• Zone A (CA, WA, NYC): $209,000-$313,000 base salary annually
• Zone B: $199,000-$297,000 base salary annually
• Zone C: $178,000-$266,000 base salary annually
• Eligible for equity in the form of RSUs