Senior ML Engineer (R14284)

Who We Are Oportun (Nasdaq: OPRT) is a mission-driven financial services company that puts its members' financial goals within reach. With intelligent borrowing, savings, and budgeting capabilities, Oportun empowers members with the confidence to build a better financial future. Since inception, Oportun has provided more than $22.7 billion in responsible and affordable credit, saved its members more than $2.5 billion in interest and fees, and helped its members set aside an average of more than $1,800 annually. A Quick Note on the Role's Focus While the title is Senior ML Engineer , this opportunity is specifically focused on ML Platform Engineering rather than ML model development or data science. We're looking for engineers with strong software engineering fundamentals and hands-on experience building, scaling, and operating the platforms and infrastructure that enable machine learning in production. The emphasis is on ML infrastructure, MLOps, model serving, platform reliability, and production engineering , rather than primarily developing, training, or fine-tuning ML models. Location Note We’re excited to consider talent currently based in India, as well as candidates who are open to relocating to India for this opportunity. Please note that, as this is a "Remote–India" position, the role must be performed from within India. The Opportunity The Machine Learning Platform team builds the software foundations that enable data scientists and machine learning engineers to develop, validate, deploy, and operate models safely and efficiently in production. In this role, you’ll lead complex platform work from business context through production outcomes, combining hands-on engineering, architectural judgment, production ownership, and mentorship. In your first year, success means leading meaningful platform initiatives, improving reliability and developer experience, and becoming a trusted technical leader for the ML platform. At Oportun, we move fast and hold each other to a high bar. You’ll partner across Data Science, Product, Risk, Fraud, and Engineering to solve ambiguous problems and move the needle for members and the business. What You'll Do Your day-to-day • You’ll lead the design, implementation, deployment, and operation of complex platform capabilities that support the machine-learning lifecycle. • You’ll design scalable systems for model deployment and serving, feature computation, data validation, workflow orchestration, monitoring, and production support. • You’ll build reusable platform components, standards, and automation while improving reliability, scalability, observability, and operational readiness across ML systems. • You’ll partner with Data Science, Product, Risk, Fraud, and Engineering teams to translate ambiguous business needs into practical technical solutions. • You’ll own significant technical initiatives end to end and lead complex production investigations—clarifying requirements, leading design, delivering safely, measuring results, and implementing durable fixes. • You’ll raise engineering quality through thoughtful code and design reviews, mentor engineers through pairing and technical guidance, and contribute to platform technical strategy. • You’ll look for ways to use AI tools thoughtfully to work smarter, reduce manual work, and make better decisions faster. Who You Are The right fit looks like this You do not need detailed implementation direction to be effective. Given an ambiguous problem and sufficient context, you can define the technical approach, explain trade-offs, align stakeholders, lead delivery, and own the outcome after launch. You’re comfortable navigating complexity and don’t wait for perfect information to move forward. You communicate clearly, give direct