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Principal Machine Learning Engineer, Recommendation Systems
hace 4 semanas
WHO ARE WE? Launch Potato is a profitable digital media company that reaches over 30M+ monthly visitors through brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. As The Discovery and Conversion Company, our mission is to connect consumers with the world’s leading brands through data-driven content and technology. Headquartered in South Florida with a remote-first team spanning over 15 countries, we’ve built a high-growth, high-performance culture where speed, ownership, and measurable impact drive success. WHY JOIN US? At Launch Potato, you’ll accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers. MUST HAVE: 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 10+ years designing, developing, and deploying large-scale machine learning systems with a focus on personalization YOUR ROLE 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. OUTCOMES 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 Champion privacy‑preserving personalization, responsible AI practices, and adaptive learning systems COMPETENCIES Visionary Thinking: Defines the future state of ML infrastructure and personalization strategy. Balances deep technical rigor with a strong understanding of product impact. Architectural Excellence: Designs scalable, modular systems that support billions of predictions and enable rapid experimentation. Sets high standards for maintainability and performance. Technical Influence: Drives decision‑making and builds consensus across teams and stakeholders without direct authority. Provides trusted guidance in ambiguous situations. Expert‑Level Execution: Navigates deep technical complexity while maintaining execution velocity. Translates research insights into production‑ready solutions. Mentorship & Leadership: Coaches senior engineers, facilitates technical reviews, and raises the technical bar for the entire organization. External Thought Leadership: Represents LP in the ML community and contributes to growing its reputation as a leader in ML innovation. Curious & Forward‑Looking: Constantly explores new approaches to personalization and actively prototypes cutting‑edge methodologies. Want to accelerate your career? Apply now Since day one, we've been committed to having a diverse, inclusive team and culture. We are proud to be an Equal Employment Opportunity company. We value diversity, equity, and inclusion. We do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. #J-18808-Ljbffr
