Launch Potato is looking to solve complex machine learning challenges and establish a technical vision for personalization, driving alignment across all ML teams and influencing strategy, architecture, and innovation
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
- Experience with graph neural networks, causal models, bandit algorithms
Responsibilities
- 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
- Represent Launch Potato’s technical brand externally through speaking engagements, open source contributions, or publications
Other
- 10+ years of experience
- Must have a strong understanding of product impact
- Ability to drive decision-making and build consensus across teams and stakeholders without direct authority
- Ability to coach senior engineers and facilitate technical reviews
- Must be committed to diversity, equity, and inclusion
