• Lead and mentor a team of AI engineers, driving technical excellence and delivery • Design and implement AI/ML solutions leveraging Azure platforms • Guide the adoption and effective use of tools like Copilot and AI Agents • Collaborate with cross-functional teams to translate business needs into AI-driven solutions • Ensure best practices in AI development, scalability, and performance

• report to a manager in Core Machine Learning within the broader Analytics group. • Build machine learning and predictive models to solve product and growth problems. • Translate business problems into technical solutions; deliver robust, low-bug software artifacts. • Collaborate with cross-functional partners to deploy models that create measurable value.

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. As a Staff Machine Learning Engineer at Liftoff, you will: - Develop and maintain machine learning models that are integral to our production decision-making system and directly influencing business outcomes. - Adopt or build new technologies for training and serving ML models (e.g. support large models, increase developer velocity, etc) - Monitor the latest ML research for functional ideas that the team could try. - Optimize ML Pipelines – Build and scale efficient pipelines for real-time and batch processing. - Model Monitoring & Improvement – Track performance, detect drift, and automate retraining. - Use strong communication skills (verbal and written) to explain statistical and machine learning concepts to both technical and non-technical audiences - Collaborate with a team of world-class engineers with diverse backgrounds. - Be part of an “engineering excellence” culture through state-of-the-art tools, risk-driven testing, explainable systems, and code review. Requirements: - 6+ years of industry experience applying Machine Learning (including neural networks) to large scale problems. - Experience with Recommendation Systems - Hands on experience with deep neural networks in production at scale. - Solid engineering and coding skills. - Track record of well-developed execution and timely delivery of projects. - Sets ego aside in pursuit of finding the best solution, no matter where it comes from. - B.S. or higher in Machine Learning, Math, Physics or similar. PhD a plus. - Experience with AdTech 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: $225,000 - $275,000 - Olympia, Austin, San Diego, Santa Barbara, Boston: $210,000 - $255,000 - All other cities and towns in our approved states: $210,000 - $255,000 #LI-EL1 We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process, we provide Covey with job requirements and candidate-submitted applications. We began using Covey Scout for Inbound on January 22, 2024. Please see the independent bias audit report covering our use of Covey here. 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.

• Drive projects forward, persuade clients, and take ownership • Deliver solutions directly at our clients’ sites — quickly, pragmatically, and with real business impact