
Personalized Recommendation Systems Leader
1 semana atrás
We're seeking an experienced Senior Machine Learning Engineer to lead the development of personalized recommendation systems.
This role offers the chance to work on complex machine learning models that directly impact user engagement and revenue at scale.
Key Responsibilities:- Design, deploy, and scale machine learning systems serving real-time recommendations across millions of user journeys
- Build and maintain efficient data processing pipelines with Spark, Beam, or Dask
- Develop ranking algorithms that balance relevance, diversity, and revenue
- Collaborate with product, engineering, and analytics teams to launch high-impact personalization features
- 5+ years building and scaling production ML systems with measurable business impact
- 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
- Track record of improving business KPIs via ML-powered personalization
- Opportunity to work on complex machine learning models with a direct impact on user engagement and revenue
- Collaborative environment with cross-functional teams
- Professional growth and development opportunities
- Technical mastery of machine learning architecture and deployment
- Experimentation infrastructure setup for rapid testing and retraining
- Impact-driven approach to designing models that move revenue, retention, or engagement
- Collaborative mindset with engineers, PMs, and analysts to scope features
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São Paulo, São Paulo, Brasil beBeeMachineLearning Tempo inteiro US$180.000 - US$200.000Job DescriptionWe're looking for a seasoned data scientist to lead the development of our recommendation systems. This is an exciting opportunity to work on large-scale machine learning projects that drive business growth through personalized experiences.
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