- Design, build, and iterate on machine learning models and LLM-based systems that power critical decisions across fraud, compliance, growth, and operations
- Work with messy, real-world data to identify signals, build features, and continuously improve model performance
- Make practical tradeoffs between model performance, interpretability, and operational cost
- Partner closely with product and operations to identify and solve problems that directly impact experience of hundreds of thousands of clients
- Contribute to backend systems and data pipelines that support model training and inference (without being primarily an infrastructure role)
- Write high-quality, tested code and participate in code reviews
- Take long-term ownership of critical systems as River scales
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