Machine Learning Engineer

About Liftoff

Liftoff is a leading AI-powered performance marketing platform for the mobile app economy. Our end-to-end technology stack helps app marketers acquire and retain high-value users, while enabling publishers to maximize revenue across programmatic and direct demand.

Liftoff’s solutions, including Accelerate, Direct, Monetize, Intelligence, and Vungle Exchange, support over 6,600 mobile businesses across 74 countries in sectors such as gaming, social, finance, ecommerce, and entertainment. Founded in 2012 and headquartered in Redwood City, CA, Liftoff has a diverse, global presence.

About the Revenue Engine Team

The Revenue Engine team works to understand the fundamental economics of the mobile ad tech marketplace, including the elasticity of demand and the effects of competition. The team of machine learning engineers, software engineers, and data analysts develops theories, validates those theories with experiments and analyses, and uses the learnings to build production systems that improve outcomes for Liftoff and its advertisers.

As a Machine Learning Engineer on the Revenue Engine Team

• Build statistical models and production systems to balance advertiser performance with business goals.
• Tune optimization parameters, measure internal competition, and model dynamic environments.
• Design and run experiments to validate theories underpinning the mobile ad tech economy.
• Develop applications in the areas of advertiser budget retention and growth, optimal margin allocation, and bidding innovations.
• Collaborate with a team of world-class engineers with diverse backgrounds as well as peers across the broader company (e.g. Operations, GTM).
• Use strong communication skills (verbal and written) to explain statistical and machine learning concepts to both technical and non-technical audiences.
• Be part of an “engineering excellence” culture through state-of-the-art tools, risk-driven testing, explainable systems, and design/code review.

Requirements

• PhD in Computer Science, Machine Learning, Economics, or a related field.
• Industry experience applying economics or machine learning to large scale problems.
• Solid engineering and coding skills.
• Excellent team communication and collaboration skills.
• Experience with ad tech is a solid plus.

Location

This role is eligible for full-time remote work in one of our entities: CA, CO, ID, IL, FL, GA, MA, MI, MN, MO, NJ, NV, NY, OR, TX, UT, and WA. We are a remote-first company with US hubs in Redwood City, Los Angeles, and New York City. Travel Expectations: We offer several opportunities for in-person team gatherings, including but not limited to project meetings, regional meetups, and company-wide events. We expect our employees to attend these gatherings at least once per quarter. These gatherings provide essential opportunities for collaboration, communication, and team building.

Compensation

Liftoff offers all employees a full compensation package that includes equity and health/vision/dental benefits associated with your country of residence. Base compensation will vary based on the candidate's location and experience. The following are our base salary ranges for this role:

• SF Bay Area, Los Angeles/Orange County, NYC, Seattle: $235,000 - $275,000
• All other cities and towns in our approved states: $215,000 - $255,000

About Liftoff and Benefits

Liftoff offers a fast-paced, collaborative, and innovative work environment where employees are empowered to grow and make an impact. We’re shaping the future of the mobile app ecosystem—join us and help accelerate what’s next. Liftoff’s compensation strategy includes competitive salaries, equity, and benefits designed to support employee well-being and performance. We benchmark compensation based on role, level, and location to ensure fairness and market alignment. Benefits may include medical coverage, wellness stipends, and additional perks based on your country of residence. Liftoff is an equal opportunity employer. We are committed to creating an inclusive environment for all employees and applicants regardless of race, ethnicity, national origin, age, marital status, disability, sexual orientation, gender identity, religion, veteran status, or any other characteristic protected by applicable law.