Machine Learning Engineer, Revenue Engine – Ad Tech

Liftoff Mobile; California (MO); On-site; USD 235,000 - 275,000; Full time

Job summary

Liftoff is seeking a Machine Learning Engineer for the Revenue Engine team, a remote-first company with US hubs in California. You will build statistical models and production systems balancing advertiser performance with Liftoff's business goals, while collaborating with a diverse engineering team.

You will apply ML to large-scale problems, design experiments, and contribute to initiatives across monetization and growth.

Qualifications

• 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.

Responsibilities

• 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 advertiser budget retention and growth, and margin allocation.
• Collaborate with engineers and cross-functional teams across the company.
• Explain statistical and ML concepts to both technical and non-technical audiences.
• Contribute to an engineering-excellence culture with modern tools and reviews.

Skills

Statistical modeling

Strong communication

Coding proficiency

Education

PhD in Computer Science / ML / Economics

Tools

Python

TensorFlow / PyTorch

Job description

Liftoff is seeking a Machine Learning Engineer for the Revenue Engine team, a remote-first company with US hubs in California. You will build statistical models and production systems balancing advertiser performance with Liftoff's business goals, while collaborating with a diverse engineering team.

You will apply ML to large-scale problems, design experiments, and contribute to initiatives across monetization and growth.