The AI Optimization Team
- We work across the ML spectrum – from traditional statistical models to cutting-edge agentic systems
- We collaborate with distributed, cross-functional teams of Engineers, Data Scientists, and Analysts in a culture that values open discussion and intellectual honesty
- We experiment with emerging techniques to push the boundaries of real-world AI capabilities and system optimization
- We value curiosity and ownership – the mindset of a researcher with the maturity to own both problems and outcomes
What You'll Do
- Design and optimize ML models that power core product experiences and drive business outcomes
- Develop statistical frameworks for A/B testing, performance monitoring, and measuring model effectiveness
- Research and implement cutting-edge techniques to enhance model accuracy, speed, and reliability
- Collaborate with product teams to optimize user experiences and translate insights into business strategy
- Build evaluation pipelines to continuously monitor and improve model performance in production
What You'll Need
- Strong statistical and ML foundation with experience in experimental design, hypothesis testing, and model optimization
- Python proficiency with data science libraries (pandas, scikit-learn, numpy, scipy)
- Machine learning expertise across supervised, unsupervised, and reinforcement learning approaches
- SQL skills for data extraction, analysis, and feature engineering
- Communication skills to translate analytical findings into clear business insights
- Ability to communicate and debate in English and Portuguese
Nice to Have
- App optimization experience with multi-armed bandits (MAB), recommendation systems, or personalization algorithms
- Analytics platform experience with tools like Amplitude, Rudderstack, or similar product analytics platforms
- MLOps familiarity with tools like MLflow for model tracking and experimentation
- Experience with Google Cloud Platform and BigQuery for large-scale data analysis
- Agentic frameworks experience with LangChain or similar tools for AI system development
Recruiting process outline:
- Online assessment: An online test to evaluate your analytical skills and statistical reasoning
- Technical interview: Deep dive into your ML experience and problem-solving approach
- Cultural interview If you are not willing to take an online quiz and work on a test case, do not apply.
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