Principal ML Engineer, Ad Performance
Job Description
Launch Potato, a thriving digital media company reaching over 30M+ monthly visitors, is seeking a Principal ML Engineer to lead their ad performance initiatives. As The Discovery and Conversion Company, they connect consumers with leading brands through data-driven content and technology. This role offers a unique opportunity to establish the technical vision for personalization, solving complex ML challenges and influencing strategy across teams. With a remote-first culture spanning 15+ countries, you'll join a high-performance environment where speed, ownership, and measurable impact drive success. The ideal candidate brings 10+ years of experience in large-scale ML systems, with expertise in personalization, deep learning, and causal inference. You'll architect systems serving billions of predictions, mentor senior engineers, and represent the company's technical excellence externally. This role combines visionary thinking with hands-on technical leadership, making it perfect for those seeking to make a significant impact in the ML space while working with a global team of high-performers.
Responsibilities For Principal ML Engineer, Ad Performance
- Define company-wide personalization strategy and architecture, driving alignment across all ML teams
- Solve critical technical challenges such as cold start, real-time learning, and exploration/exploitation tradeoffs
- Design and implement advanced ML solutions using cutting-edge techniques
- Create and enforce ML architecture patterns, design standards, and reusable infrastructure across teams
- Lead multi-quarter, cross-functional initiatives that redefine how personalization impacts business KPIs
- Act as technical mentor to senior ML engineers
- Represent Launch Potato's technical brand externally
- Champion privacy-preserving personalization, responsible AI practices, and adaptive learning systems
Requirements For Principal ML Engineer, Ad Performance
- Expertise building ML systems with deep expertise in large-scale personalization
- Recognized industry expertise through patents, publications, or significant product impact
- Proven success architecting ML platforms serving billions of predictions in production
- Demonstrated track record of 0→1 innovation in personalization or recommender systems
- Mastery across multiple ML domains including deep learning, causal inference, multi-armed bandits, and graph-based models
- 10+ years designing, developing, and deploying large-scale machine learning systems
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