Machine Learning Engineer, Revenue+, Level 5

Snap; 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

Job summary

Snap Inc. is seeking a founding Machine Learning Engineer for the Revenue+ team to establish ML as a core capability for Snapchat+ monetization.

You will tackle personalization, offer decisioning, retention, and lifecycle optimization at large scale, collaborating with product and engineering to drive revenue growth. The role requires strong ML foundations, product sense, and ownership of end-to-end ML initiatives, with equity in RSUs and a pay structure reflecting multiple zones in the U.S.

Qualifications

• Bachelor's degree in a technical field or equivalent practical experience.
• 5+ years of post-Bachelor’s machine learning experience or equivalent combinations (MS/PhD).
• Experience deploying ML systems for ranking, recommendation, personalization, or monetization.
• Ability to take ML problems from ambiguous statements to production solutions.

Responsibilities

• Identify high-value ML opportunities to drive subscription growth, monetization, and retention.
• Design, build, and deploy ML systems for personalization, ranking, and lifecycle optimization.
• Own end-to-end work from problem framing to production deployment and measurement.
• Set technical direction for a new Revenue+ ML capability and guide best practices.
• Collaborate with Product, Data Science, Backend, and Mobile Engineering to shape ML investments.
• Build reliable, observable ML systems that scale to Snapchat’s user base.

Skills

ML foundations

Product judgment

ML systems

Autonomy

Collaboration

Education

Bachelor's degree in CS or related field

Job description

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.

What you’ll do

• 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

Knowledge, Skills & Abilities

• 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

Minimum Qualifications

• 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

Preferred Qualifications

• 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

Default Together Policy at Snap

At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration.

To reflect this, we practice a “default together” approach and expect our team members to work in an office 4+ days per week.

At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate.

Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable).

Our Benefits

Snap Inc. is its own community, so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms.

• paid parental leave
• comprehensive medical coverage
• emotional and mental health support programs
• compensation packages that let you share in Snap’s long‑term success!

Compensation

In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate’s starting pay will be determined based on job‑related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future.

• Zone A (CA, WA, NYC): The base salary range for this position is $209,000-$313,000 annually.
• Zone B: The base salary range for this position is $199,000-$297,000 annually.
• Zone C: The base salary range for this position is $178,000-$266,000 annually.

This position is eligible for equity in the form of RSUs.

If you believe this job description is missing required pay transparency information, please submit the report through the form: Job Description Pay Range Disclosure.

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