machine learning engineer (prefr)

prefr (a brand under DTPL) is a tech-first fintech platform reshaping how India’s digital-first generation experiences credit. we currently offer instant personal loans from ₹50,000 to ₹5,00,000 through a seamless, end-to-end digital journey — serving India’s creditworthy yet underserved segments, in partnership with RBI-approved top-tier financial institutions. our mission to become the largest platform for delivering fast, transparent and trusted credit for the millions - by bringing together.distribution depth, AI-driven intelligence & multi-lender access.   about the role we are looking for a passionate and technically strong ai/ml engineer to join our core team driving the intelligence behind our lending platform. this is an l4-level role where you'll build high-performance ml frameworks, scale decision systems, and lay the foundation for the next evolution: agentic ai systems that autonomously extract insights, support business decisions, and power internal copilots. if you are someone who enjoys solving hard problems at the intersection of software engineering and ml, and are excited about the future of ai agents in real-world systems, we want to hear from you. what will you do: • own and evolve core frameworks powering the loan decision-making process across the company including but not limited to user approval and eligibility frameworks • design, develop, and optimize scalable ml infrastructure and software frameworks that integrate seamlessly with production systems • partnering with senior engineers and domain leads to lay groundwork for agentic systems – from auto-insight generation to internal decision copilots (e.g., ai for bi) • help develop data and model lifecycle: from ingestion and feature engineering to deployment and monitoring • build generalized systems that support multi-tenant use across verticals be it policy or data for analytics • continuously monitor production performance to ensure that live systems behave as expected, and proactively propose improvements • document learnings, scale reusable patterns, and drive adoption of best practices in ml system design you should apply if: • have 4+ years of experience building production-grade software systems in java / scala / python • have familiarity with ml lifecycle and deployment practices, even if not deep modeling experience • exhibit deep business understanding by translating technical capabilities into impactful solutions, ensuring that frameworks contribute directly to business outcomes • are comfortable working in a fast-paced, startup environment and taking end-to-end ownership • possess a strong sense of compounding, capable of building modular, iterative solutions that grow in capability over time, especially in the context of agentic ai frameworks must have • 3+ hands-on experience with developing frameworks from scratch: sdks, and platforms that touched ml systems and served multiple internal teams • have 4+ years of experience building production-grade software systems in scala / python • strong grasp of oop design, system architecture, and ml pipeline design • demonstrated ability to take a messy real-world problem and build reliable, scalable ml systems around it • builds both production-grade ml systems and internal ml and ai frameworks that enhance team productivity, with a focus on delivering overall impact • proven ability to work in cross-functional environments, with direct exposure to business and product stakeholders, collaborating closely with data scientists and data engineers to deliver ml systems—not limited to sde-only interfaces • adaptable across changing tech stacks and problem spaces, with a bias toward building missing systems and infrastructure when needed