Principal Machine Learning Engineer, Ad Performance
Job Description
Launch Potato, a thriving digital media company, is seeking a Principal Machine Learning Engineer to lead their Ad Performance initiatives. As The Discovery and Conversion Company reaching over 30M+ monthly visitors, we're looking for an exceptional ML leader to establish the technical vision for personalization. This role combines deep technical expertise with strategic leadership, requiring 10+ years of experience in designing and deploying large-scale ML systems. You'll work with a remote-first team spanning 15+ countries, driving innovation in personalization, recommender systems, and advanced ML solutions. The ideal candidate will have proven success with platforms serving billions of predictions, expertise in multiple ML domains, and a track record of significant product impact. This role offers the opportunity to shape the future of personalization technology while mentoring senior engineers and representing Launch Potato in the broader ML community. The position combines technical depth with strategic influence, making it perfect for those who want to drive meaningful impact at scale while working with a high-performance, global team.
Responsibilities For Principal Machine Learning 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
- Lead multi-quarter, cross-functional initiatives
- 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 Machine Learning 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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