Personalization Systems Architect

1 semana atrás

São Paulo, São Paulo, Brasil beBeeMachine Tempo inteiro US$120.000 - US$150.000

As a seasoned Machine Learning Engineer, you will play a pivotal role in crafting the personalization engine behind our esteemed portfolio of brands.

Our ideal candidate will design, deploy, and scale ML systems that power real-time recommendations across millions of user journeys. This is an extraordinary opportunity to work on systems serving 100M+ predictions daily, directly impacting engagement, retention, and revenue at scale.

Key responsibilities include driving business growth by building and optimizing recommendation systems that personalize experiences for millions of users daily. You will own the modeling, feature engineering, data pipelines, and experimentation that make personalization smarter, faster, and more impactful.

Specifically, your mission will involve:

  • Building and deploying ML models serving 100M+ predictions per day to personalize user experiences at scale
  • Enhancing data processing pipelines (Spark, Beam, Dask) with efficiency and reliability improvements
  • Designing ranking algorithms that balance relevance, diversity, and revenue
  • Delivering real-time personalization with latency < 50ms across key product surfaces
  • Running statistically rigorous A/B tests to measure true business impact
  • Optimizing for latency, throughput, and cost efficiency in production
  • Partnering with product, engineering, and analytics to launch high-impact personalization features
  • Implementing monitoring systems and maintaining clear ownership for model reliability
Requirements

To succeed in this role, you must possess:

  • 5+ years of experience building and scaling production ML systems with measurable business impact
  • Experience deploying ML systems serving 100M+ predictions daily
  • A strong background in ranking algorithms (collaborative filtering, learning-to-rank, deep learning)
  • Proficiency with Python and ML frameworks (TensorFlow or PyTorch)
  • Skilled with SQL and modern data warehouses (Snowflake, BigQuery, Redshift) plus data lakes
  • Familiarity with distributed computing (Spark, Ray) and LLM/AI Agent frameworks
  • A track record of improving business KPIs via ML-powered personalization
  • Experience with A/B testing platforms and experiment logging best practices
Competencies

The ideal candidate should demonstrate:

  • Technical mastery: In-depth knowledge of ML architecture, deployment, and tradeoffs
  • Experimentation infrastructure: Ability to set up systems for rapid testing and retraining (MLflow, W&B)
  • Impact-driven: Design models that drive revenue, retention, or engagement
  • Collaborative: Thrive working with engineers, PMs, and analysts to scope features
  • Analytical thinking: Break down data trends and design rigorous test methodologies
  • Ownership mentality: Own your models post-deployment and continuously improve them
  • Execution-oriented: Deliver production-grade systems quickly without sacrificing rigor
  • Curious and innovative: Stay on top of ML advances and apply them to personalization

Join our team of passionate professionals who are dedicated to delivering cutting-edge solutions. We offer a dynamic and inclusive work environment that fosters growth, creativity, and innovation.

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