Liftoff

Machine Learning Engineer

USA, United States full-time Mid Salary not listed
full-time Mid level Technology & IT Curated
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About the role

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, you will:

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:
The preferred location for this role is within California.

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

#LI-EL1

#LI-REMOTE

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.

Agency and Third Party Recruiter Notice:

Liftoff does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or Recruiting Team. All candidates must be submitted via our Applicant Tracking System by approved Liftoff vendors who have been expressly requested to make a submission by our Recruiting Team for a specific job opening. No placement fees will be paid to any firm unless such a request has been made by the Liftoff Recruiting Team and such a candidate was submitted to the Liftoff Recruiting Team via our Applicant Tracking System.

Interview prep

Walk in with sharper answers.

Use this as a quick practice sheet before you speak with the employer.

Mid
Technology & IT Digital Marketing Finance Operations Remote Collaboration Mid level full-time

Likely questions

  1. Tell us about work you have done that is close to the Machine Learning Engineer role.
  2. How would you approach your first 30 days at Liftoff?
  3. Which of Digital Marketing, Finance and Operations have you used recently, and what did it help you achieve?
  4. Describe a time you solved a problem without waiting to be told exactly what to do.
  5. How do you handle busy days, changing priorities, or pressure at work?

Prepare before the call

  • A recent example that proves your experience with Digital Marketing, Finance and Operations.
  • One short story with a problem, your action, and the result.
  • Two examples that show the strengths listed on your CV.
  • A clear reason why this role and company interest you.
  • Your availability, preferred work style, and salary expectations.

Ask them

  • What would success look like in the first 90 days?
  • What are the main problems this hire should help solve?
  • How does the team give feedback and measure good work?
  • What does a normal working week look like for this role?
Practice line

I am interested in the Machine Learning Engineer role because I can bring practical experience in Digital Marketing, Finance and Operations, learn the team quickly, and contribute to the outcomes Liftoff needs from this hire.

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