Machine Learning Engineer

Job Summary

At Prodigal, we are building AI Agents for loan servicing and collections. Founded in 2018 by IITB alumni, our journey began when our founders Shantanu and Sangram faced the antiquated the $13B+ lending/collections industry was mostly using pen and paper and decided to build the first real intelligence layer for debt recovery.

Today, we stand at the forefront of a seismic shift in the industry, building Agentic AI applications for loan servicing and collections. Powered by our cutting-edge platform, Prodigal s Intelligence Engine (PIE), we re creating the next-generation agentic workforce - one that empowers companies to achieve unprecedented levels of operational excellence and intelligence.

With over 100+ enterprise customers across North America and backing from Y Combinator, Accel and Menlo Ventures, we are the fastest growing AI company in consumer finance.

What You'll Do

• Work across a range of ML problems - Voice, Data, Recommendations, Infrastructure, LLMs, Product.
• Train LLMs for AI agents used for consumer finance.
• Develop evals, harnesses, and monitoring systems.
• Own major technical areas with significant autonomy, from problem definition to production deployment

What You Bring

• 2 - 5 years of hands-on engineering experience, with good exposure to building or working with ML or AI systems in production.
• Solid Python fundamentals - you are comfortable writing clean, maintainable code and debugging production issues.
• Some experience working with LLMs: prompt engineering, API integrations, or building simple pipelines or agents.
• High bias for action - you dont wait to be told exactly what to do, and you push yourself to ship rather than over-engineer.
• Eager to learn in a fast-moving environment, take ownership of your work, and ask good questions.

Why This Role

• Real ownership from day one: ML team is a small pod. You wont be a cog - youll own components, ship features, and see your work in live consumer conversations within weeks.
• Frontier work: AI that reasons, decides, and acts is one of the hardest problems in applied AI. Youll be learning by doing on problems most engineers never touch.
• Strong mentorship: youll work directly with senior engineers and the ML Lead who will invest in your growth - this is a place to level up fast.
• High leverage early career: the decisions you make and the code you write will impact millions of financial conversations. Rare for an early-career role.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.