Founding ML Engineer for Revenue+ Monetization

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

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.