Principal ML Engineer, Ad Performance
Job Description
Launch Potato, a thriving digital media company, is seeking a Principal ML 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 building 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 position offers the opportunity to shape the company's ML architecture, mentor senior engineers, and contribute to the broader ML community while working on systems serving billions of predictions. Our high-performance culture emphasizes speed, ownership, and measurable impact. The ideal candidate will bring expertise in deep learning, causal inference, and graph-based models, while championing privacy-preserving AI practices. This role represents a unique opportunity to drive technical innovation at scale 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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