Machine Learning Engineer, Revenue+

Snapchat, Inc.; New York (NY); On-site; USD 209,000 - 313,000; Full time

Benefits offered by this job

Paid parental leave

Comprehensive medical coverage

Emotional and mental health support

Compensation packages

Job summary

Snapchat, Inc. is hiring a founding Machine Learning Engineer for the Revenue+ team in New York, onsite, to build ML as a core capability for subscription growth and monetization across Snapchat+.

The role focuses on personalization, ranking, propensity modeling, and lifecycle optimization, driving end-to-end ML ownership and collaboration with Product, DS, Backend, and Mobile Engineering to shape product strategy.

Qualifications

• Strong foundation in ML and software engineering.

Responsibilities

• Identify high-value ML use cases to boost subscription growth and monetization.
• Build ML systems for personalization, ranking, propensity modeling, and lifecycle optimization.
• Own projects end-to-end from data exploration to production deployment and measurement.
• Set technical direction for the Revenue+ ML capability.
• Collaborate with Product, Data Science, Backend, and Mobile Engineering to shape ML investments.
• Build reliable, observable, and scalable ML systems for Snapchatters.
• Use AI tools to accelerate development while ensuring code correctness, security, and production quality.

Skills

Machine learning

Software engineering

Product and business judgment

Ranking

Recommendation

Personalization

Propensity modeling

Decisioning

Monetization

Retention

End-to-end ownership

Collaboration

Mentorship

AI tools

Education

Bachelor’s Degree in Computer Science

Master’s degree in CS

Advanced degree in CS

Tools

TensorFlow

PyTorch

Job description

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