Launch Potato is seeking to connect consumers with the world’s leading brands through data-driven content and technology by solving complex machine learning challenges in personalization at scale.
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.
- 10+ years designing, developing, and deploying large-scale machine learning systems with a focus on personalization.
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
- 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.
- Constantly explores new approaches to personalization and actively prototypes cutting-edge methodologies.
- Balances deep technical rigor with a strong understanding of product impact.
