Machine Learning Decisioning Developer Jobs

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1d ago

Machine Learning Engineer, Revenue+

Snapchat New York, NY

New York, NY

1d ago

$178k - $313k/yr Full time Engineer Growth, Retention & Monetization Machine Learning

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Job Description

Snap is building out machine learning capability across subscription growth and monetization for Snapchat+. As a founding Machine Learning Engineer for the Revenue+ team, you will help define how ML supports personalized paywalls, offer decisioning, retention, lifecycle optimization, and subscriber value, with ownership spanning problem framing through production and measurement. The role is based in New York, NY (onsite) and expects in-office presence 4+ days per week.

Role summary

You will identify where machine learning can drive meaningful, incremental improvements to subscription growth and monetization. You will then design, build, and deploy production-ready ML systems that enable personalization and decisioning across the subscriber lifecycle, while establishing a durable technical foundation for a new Revenue+ ML capability.

Responsibilities

Find 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 end-to-end process from ambiguous business problems and data exploration to experimentation, production deployment, measurement, and iteration
Define technical direction and best practices for establishing a new Revenue+ ML capability
Partner with Product, Data Science, Backend, and Mobile Engineering to shape product strategy and prioritize ML investment areas
Build reliable, observable, scalable production ML systems serving Snapchatters at significant scale
Use AI tools to accelerate development while maintaining rigorous standards for code correctness, security, and production reliability

Requirements

Strong understanding of machine learning and software engineering foundations
Strong product and business judgment, including the ability to pinpoint where ML can deliver measurable incremental value
Experience with ranking, recommendation, personalization, propensity modeling, decisioning, or related product ML systems
Ability to translate ambiguous business problems into concrete ML opportunities and technical plans
Ability to work with substantial autonomy and take end-to-end technical ownership
Strong collaboration and mentorship skills
Proficiency in leveraging AI tools to streamline development, paired with 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 year of post-grad machine learning 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 and into production

Benefits

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

Compensation

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

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