Responsibilities
- Work on machine-learning problems across voice, data, recommendations, infrastructure, LLMs, and product
- Train LLMs for AI agents used in consumer finance
- Develop evaluation systems, harnesses, and monitoring systems
- Own major technical areas from problem definition through production deployment
- Design ML systems, fine-tune and integrate LLMs, tune prompts, and debug real-time production issues
Requirements
- 2–5 years of hands-on engineering experience with exposure to ML or AI systems in production
- Strong Python fundamentals, including clean, maintainable code and production debugging
- Some experience with LLMs, prompt engineering, API integrations, or simple pipelines or agents
- Ability to learn quickly, take ownership, respond to feedback, and ship in a fast-moving environment
Benefits
- Small ML team with ownership of components and features from day one
- Work on frontier agentic AI problems in live consumer-finance conversations
- Direct mentorship from senior engineers and the ML Lead
- High-impact work affecting millions of financial conversations
About Prodigal
Prodigal maximizes payments for lenders and debt collectors by building dynamic strategies and motivating consumers with highly engaging, personalized treatments. Our advanced genAI has been trained on over 400 million consumer finance conversations, delivering unmatched industry expertise so you can drive record recovery rates. Experience the power of intelligent debt resolution with Prodigal’s AI that pays. Prodigal is headquartered in Mountain View, California, and our global team is on a mission to build the intelligence layer that powers consumer finance. With the backing of domain experts, technology leaders, and top investors, including Accel, Menlo Ventures, and Y-Combinator, Prodigal is poised to become the next iconic vertical SaaS company.