Machine Learning Engineer (Revenue+)

SNAP, Inc.; New York (NY); On-site; USD 180,000 - 300,000; Full time

Benefits offered by this job

Parental leave

Fertility support

Back-up child care

Health insurance

401(k) with company match

Well-being programs

Gym discounts

Mental health support

Education subscriptions

Job summary

SNAP, Inc. is seeking a founding Machine Learning Engineer for the Revenue+ team to establish ML as a core capability for subscription growth, monetization, and the Snapchat+ product.

You will design, build, and deploy ML systems for personalization, ranking, propensity modeling, and lifecycle optimization, owning the path from problem to production while partnering with Product, Data Science, Backend, and Mobile teams to drive measurable revenue impact.

Qualifications

• Experience with ranking, recommendation, personalization, propensity modeling, decisioning, or related product ML systems
• Strong understanding of machine learning and software engineering foundations
• Proficiency in leveraging AI tools to streamline development, with the ability to audit generated output for architectural integrity, performance bottlenecks, and security risks
• Ability to operate with substantial autonomy and take end-to-end technical ownership
• Ability to independently turn ambiguous business problems into concrete ML opportunities and technical plans
• Strong collaboration and mentorship skills
• Strong product and business judgment, with the ability to identify where ML can create measurable incremental value
• Experience developing and productionizing machine learning systems for monetization, retention, or other relevant product ML applications
• Experience taking ML systems from ambiguous problem statements through experimentation and into production
• 5+ years of post-Bachelor’s ML experience; or Master’s +4; or PhD +1
• Bachelor’s Degree in CS or related field; Advanced degree preferred

Responsibilities

• Identify high-value opportunities where ML 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

Skills

ML engineering

Ranking systems

Recommendation

Personalization

Propensity modeling

Decisioning

Experimentation

End-to-end ownership

Autonomy

Education

Bachelor's Degree in CS or related field

Advanced degree (MS/PhD) in CS or related field

Job description

• 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
• 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

• Up to 28 weeks of parental leave and return-to-work program
• Adoption, surrogacy, infertility, and fertility preservation benefits
• Backup child care coverage, center-based care support, & caregiver assistance
• Dependent Daycare Flexible Spending Account
• Lactation rooms (based on office location) and breastmilk shipping coverage
• Services to support your path to parenthood & beyond - fertility support & family planning via Carrot, SNOO, Hinge Health
• Short-term disability, long-term disability, basic life insurance, and AD&D insurance
• For Snap, employees taking care of loved ones with complex, chronic, or ongoing care needs (i.e. parent with Dementia, spouse with Cancer, child with Autism), your family can save time, money, & stress with Wellthy
• Comprehensive medical coverage, including PPO, HDHP with HSA, and HMO options
• Dental coverage, including orthodontia benefits
• Vision coverage, including frame and contact allowance and LASIK benefits
• Free membership to One Medical for primary and urgent healthcare services
• Business Travel Insurance
• Gym perks and discounts
• Team fitness classes and races
• Sports leagues
• Cooking and nutritional workshops
• Well-being reimbursement
• Unlimited access to virtual physical therapy with Anthem
• 15 sessions per year of mental health for you + dependents through Lyra
• Generous time off and leave programs. In the US, this includes the following:
• Up to 3 weeks (120 hours) of vacation time and 1 floating holiday for non-exempt team members
• 12 paid holidays per year
• 15 sick and safe days per year
• Social gatherings, team outings, and volunteering programs
• Speaker series, classes, and subscriptions to educational programs
• Meditation and yoga classes
• Snap Inc. provides a 401(k) plan that allows you to save on a pre‑tax, Roth, and after‑tax basis for your retirement (yes, we even have the Mega backdoor option!) Snap will also match 100% up to 3% of your contribution and then 50% on your 4th and 5th%
• Flexible Spending Accounts for healthcare, daycare and commuter
• Health Savings Account with employer contributions
• Rocket Lawyer memberships
• Financial education programs
• Snap exclusive discounts and perks
• Compensation packages that let you share in Snap's long-term success!

Experience with ranking, recommendation, personalization, propensity modeling, decisioning, or related product ML systemsStrong understanding of machine learning and software engineering foundationsProficiency 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 risksAbility to operate with substantial autonomy and take end-to-end technical ownershipAbility to independently turn ambiguous business problems into concrete ML opportunities and technical plansStrong collaboration and mentorship skillsStrong product and business judgment, with the ability to identify where ML can create measurable incremental valueExperience developing and productionizing machine learning systems for ranking, recommendation, personalization, propensity modeling, decisioning, monetization, retention, or other relevant product ML applicationsExperience taking ML systems from ambiguous problem statements through experimentation and into production5+ 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 experienceBachelor’s Degree in a relevant technical field such as computer science or equivalent years of practical work experienceAdvanced degree in computer science or related fieldExperience with subscription, monetization, pricing, offers, retention, or lifecycle optimizationExperience with causal inference, uplift modeling, experimentation, customer lifetime value, or incremental impact measurementExperience of extensive collaboration with Backend and Mobile SWEsExperience optimizing ML systems against business or revenue outcomesExperience operating production ML systems at significant scaleExperience as an early or founding ML engineer, or in another environment requiring broad technical and product ownership