Stuut is transforming accounts receivable for B2B companies by making collections smarter and faster, addressing the inefficiencies and costs associated with historically manual processes.
Requirements
- Are fluent in Python and experienced with ML frameworks like TensorFlow or PyTorch.
- Have deployed deep learning, transformer, or retrieval-augmented generation (RAG) models in production.
- Understand MLOps, scalable infrastructure, model serving, and monitoring.
- Care about responsible AI—bias mitigation, privacy, and safety.
Responsibilities
- Design, implement, and ship machine learning models tailored to financial workflows—moving from concept to production.
- Partner with product managers, engineers, and domain experts to deeply understand workflows and translate them into scalable AI solutions.
- Build robust data pipelines, fine-tune model performance, and ensure solutions meet production-grade reliability and efficiency standards.
- Monitor, debug, and improve deployed models to ensure ongoing accuracy, relevance, and business value.
- Contribute technical leadership through code reviews, mentorship, and best practice sharing.
- Design, build, and deploy AI models that redefine how financial operations run—starting with accounts receivable.
- Fine-tune smaller models for real-world workflows, and ensure every deployment is production-ready and driving measurable value.
Other
- Hold a Master’s or Ph.D. in Machine Learning, Computer Science, or a related field—or have equivalent hands-on experience.
- Are a strong collaborator with clear communication skills and technical humility.
- Thrive in a fast-moving, high-growth startup environment.
