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 bring deep expertise in ML domains including deep learning, causal inference, multi-armed bandits, and graph-based models, with a proven track record of innovative solutions that have made significant product impact.
As Principal ML Engineer, you'll establish the technical vision for personalization across Launch Potato, solving complex challenges like cold start problems and real-time learning while balancing exploration/exploitation tradeoffs. You'll architect ML platforms capable of serving billions of predictions, create reusable infrastructure, and drive alignment across all ML teams.
The position offers a competitive compensation package ranging from $160,000 to $250,000 per year, with additional profit-sharing bonuses. Working in a remote-first environment with a global team spanning 15+ countries, you'll have the opportunity to make measurable impact while advancing your career in a high-performance culture that values speed and ownership.
This role is perfect for a visionary technical leader who can balance deep technical rigor with product impact, mentor senior engineers, and represent Launch Potato's technical excellence through external thought leadership. If you're passionate about building cutting-edge personalization systems and want to shape the future of how millions of users discover content, this role offers an exceptional opportunity to drive innovation at scale.
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
- 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
Benefits For Principal Machine Learning Engineer, Recommendation Systems
- Profit-sharing bonus
- Competitive benefits package
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