Machine Learning Engineer, Revenue+, Level 5
About The Position
Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services. Snap Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We’re deeply committed to the well-being of everyone in our global community, which is why our values are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront. We’re looking for a founding Machine Learning Engineer to join the Revenue+ team and help establish machine learning as a core capability for subscription growth and monetization across Snapchat+ subscription. You’ll work on problems such as personalized paywalls, offer decisioning, retention, lifecycle optimization, and subscriber value, with direct and measurable impact on revenue.
Requirements
- Strong understanding of machine learning and software engineering foundations
- Strong product and business judgment, with the ability to identify where ML can create measurable incremental value
- Experience with ranking, recommendation, personalization, propensity modeling, decisioning, or related product ML systems
- Ability to independently turn ambiguous business problems into concrete ML opportunities and technical plans
- Ability to operate with substantial autonomy and take end-to-end technical ownership
- Strong collaboration and mentorship skills
- Proficiency in, or a strong aptitude for, leveraging AI tools to streamline development, paired with the critical judgment to audit generated output 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 + 4+ year of post-grad machine learning experience; or PhD in a relevant technical field + 1 years 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 ML applications
- Experience taking ML systems from ambiguous problem statements through experimentation and into production
Nice To Haves
- Advanced degree in computer science or related field
- Experience with subscription, monetization, pricing, offers, retention, or lifecycle optimization
- Experience of extensive collaboration 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 environment requiring broad technical and product ownership
Responsibilities
- Identify high-value opportunities 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
- Own the full path from ambiguous business problem and data exploration through experimentation, production deployment, measurement, and iteration
- Establish technical direction and best practices for a new Revenue+ ML capability
- Partner closely with Product, Data Science, Backend, and Mobile Engineering to shape product strategy and prioritize ML investments
- Build reliable, observable, scalable production ML systems serving Snapchatters at significant scale
- Utilize AI tools to design and ship scalable services while upholding rigorous standards for code correctness, security, and production
Benefits
- paid parental leave
- comprehensive medical coverage
- emotional and mental health support programs
- compensation packages that let you share in Snap’s long-term success
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What This Job Offers
Job Type
Full-time
Career Level
Senior
