Machine Learning Engineer (AdTech)

Location: Remote within approved US states: California, Colorado, Idaho, Illinois, Florida, Georgia, Massachusetts, Michigan, Minnesota, Missouri, New Jersey, Nevada, New York, Oregon, Pennsylvania, Texas, Utah, and Washington. Quarterly in-person team gatherings are expected.

Base salary: $210,000–$275,000 per year, depending on location and experience.

Company

AI-powered performance marketing platform supporting mobile app businesses through user acquisition, retention, monetization, and programmatic advertising technology.

What you will do

• Develop and maintain production machine learning models that support decision-making and business outcomes.
• Build or adopt technologies for training and serving machine learning models, including support for large models.
• Design and scale efficient machine learning pipelines for real-time and batch processing.
• Monitor model performance, detect drift, and automate retraining and improvement workflows.
• Evaluate current machine learning research and apply relevant ideas to production systems.
• Explain statistical and machine learning concepts to technical and non-technical audiences while collaborating with engineers.

Requirements

• 6+ years of industry experience applying machine learning, including neural networks, to large-scale problems.
• Production experience with deep neural networks at scale.
• Experience with recommendation systems.
• Strong engineering and coding skills with a record of executing and delivering projects on time.
• Bachelor’s degree or higher in machine learning, mathematics, physics, or a related field.
• Ability to communicate clearly and collaborate effectively across engineering teams.

Nice to have

• PhD in machine learning, mathematics, physics, or a related field.
• AdTech experience.

Culture & Benefits

• Remote-first work environment with US hubs in Redwood City, Los Angeles, and New York City.
• Quarterly opportunities for project meetings, regional meetups, and company-wide events.
• Engineering excellence practices including state-of-the-art tools, risk-driven testing, explainable systems, and code review.
• Equity and health, vision, and dental benefits.
• Collaborative, fast-paced environment focused on innovation and employee growth.