Principal Machine Learning Engineer, Recommendation Systems
Job Description
Launch Potato, a thriving digital media company reaching over 30M+ monthly visitors, is seeking a Principal Machine Learning Engineer to lead their recommendation systems initiatives. As The Discovery and Conversion Company, they connect consumers with leading brands through data-driven content and technology.
The role demands an exceptional leader with 10+ years of experience in designing and deploying large-scale machine learning systems, particularly in personalization. The ideal candidate will have demonstrated expertise through patents, publications, or significant product impact, and possess mastery across multiple ML domains including deep learning, causal inference, and graph-based models.
As the Principal ML Engineer, you'll establish the technical vision for personalization at Launch Potato, solving complex challenges like cold start problems and real-time learning. You'll lead cross-functional initiatives, mentor senior engineers, and represent the company's technical excellence externally. The position offers the opportunity to work with cutting-edge ML techniques while driving measurable business impact.
The company offers a competitive compensation package ranging from $160,000 to $250,000 per year, plus profit-sharing bonuses and benefits. Based in South Florida but operating remote-first, Launch Potato has built a high-performance culture spanning 15+ countries where speed, ownership, and measurable impact drive success.
This role is perfect for a visionary ML leader who can balance deep technical expertise with business acumen, design scalable systems serving billions of predictions, and champion privacy-preserving personalization practices. You'll have the opportunity to shape the future of personalization technology while working with a global team of high-performers in a fast-paced, impact-driven environment.
Responsibilities For Principal Machine Learning Engineer, Recommendation Systems
- 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 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 Machine Learning Engineer, Recommendation Systems
- 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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