Machine Learning Engineer, Revenue+, Level 5

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. Were 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.

Were 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. Youll work on problems such as personalized paywalls offer decisioning retention lifecycle optimization and subscriber value with direct and measurable impact on revenue.

What youll 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:

• Bachelors Degree in a relevant technical field such as computer science or equivalent years of practical work experience
• 5 years of post-Bachelors machine learning experience; or Masters 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 weve 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. Our benefits are built around your needs and include paid parental leave comprehensive medical coverage emotional and mental health support programs and compensation packages that let you share in Snaps 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 candidates 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):

Zone B:

Zone C:

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