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

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