Launch Potato is seeking to solve complex machine learning challenges related to personalization and recommendation systems to enhance their digital media platform's ability to connect consumers with leading brands through data-driven content and technology.
Requirements
- 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
- Experience designing, developing, and deploying large-scale machine learning systems with a focus on personalization
- Ability to translate research insights into production-ready solutions
Responsibilities
- Establish the technical vision for personalization at Launch Potato, solving the company’s most complex ML challenges and influencing strategy, architecture, and innovation across teams.
- 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 (e.g., graph neural networks, causal models, bandit algorithms).
- 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, guiding complex decision-making and scaling team capability.
Other
- 10+ years designing, developing, and deploying large-scale machine learning systems with a focus on personalization
- Represent Launch Potato’s technical brand externally through speaking engagements, open source contributions, or publications
- Champion privacy-preserving personalization, responsible AI practices, and adaptive learning systems
- Mentorship & Leadership: Coaches senior engineers, facilitates technical reviews, and raises the technical bar for the entire organization
- Equal Employment Opportunity company committed to diversity, equity, and inclusion
