Chief Personalization Strategist

2 semanas atrás

Rio de Janeiro, Rio de Janeiro, Brasil beBeeEngineer Tempo inteiro US$160.000 - US$220.000
Job Summary

A visionary Principal Machine Learning Engineer is sought to drive the development of cutting-edge personalization systems and lead a team of high-performing engineers.

This role requires expertise in building large-scale ML systems, architecting modular platforms, and designing scalable solutions that support billions of predictions. The ideal candidate will have a proven track record of innovation and impact in personalization or recommender systems.

Key Responsibilities
  • Define the technical vision for personalization and develop strategies to drive alignment across all ML teams.
  • Solve complex technical challenges such as cold start, real-time learning, and exploration/exploitation tradeoffs.
  • Design and implement advanced ML solutions using graph neural networks, causal models, and bandit algorithms.
  • Lead cross-functional initiatives to redefine how personalization impacts business KPIs.
Requirements
  • 10+ years of experience designing, developing, and deploying large-scale machine learning systems with a focus on personalization.
  • Expertise in building ML systems with deep expertise in large-scale personalization.
  • Recognized industry expertise through patents, publications, or significant product impact.
  • 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.
Benefits
  • Opportunity to work with a global team of high-performers.
  • Chance to accelerate career growth by owning outcomes, moving fast, and driving impact.
  • Access to AI-powered advice and exclusive features.
Competencies
  • Visionary Thinking: Defines the future state of ML infrastructure and personalization strategy.
  • Architectural Excellence: Designs scalable, modular systems that support billions of predictions.
  • Technical Influence: Drives decision-making and builds consensus across teams and stakeholders.
  • Expert-Level Execution: Navigates deep technical complexity while maintaining execution velocity.
  • Mentorship & Leadership: Coaches senior engineers and raises the technical bar for the entire organization.
  • External Thought Leadership: Represents the company in the ML community and contributes to growing its reputation.
  • Curious & Forward-Looking: Constantly explores new approaches to personalization and actively prototypes cutting-edge methodologies.

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