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Launch Potato Logo

Principal ML Engineer, Ad Performance

Launch Potato

$160,000 - $250,000
Sep 4, 2025
Columbus, OH, US
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Launch Potato is looking to solve the company's most complex ML challenges and influence strategy, architecture, and innovation across teams by establishing the technical vision for personalization.

Requirements

  • Expertise building ML systems with deep expertise in large-scale personalization
  • 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
  • Designs scalable, modular systems that support billions of predictions and enable rapid experimentation.
  • Translates research insights into production-ready solutions.

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

  • Recognized industry expertise through patents, publications, or significant product impact
  • Balances deep technical rigor with a strong understanding of product impact.
  • Drives decision-making and builds consensus across teams and stakeholders without direct authority.
  • Coaches senior engineers, facilitates technical reviews, and raises the technical bar for the entire organization.
  • Contributes to growing its reputation as a leader in ML innovation.