To build an enterprise-grade ML platform that powers SoFi's fraud detection and risk mitigation use cases, and provides scalable, self-serve capabilities that can be leveraged by teams across the company.
Requirements
4+ years programming experience, ideally on a modern tech stack.
Experience building and maintaining distributed systems or microservices at scale.
Strong understanding of data infrastructure and working with relational databases (e.g., PostgreSQL) and/or big data systems.
Hands-on experience with cloud platforms (AWS preferred) and containerization (Docker, Kubernetes).
Familiarity with ML workflows, including model training, batch/online inference, or feature pipelines.
Strong sense of ownership; ability to take a project from inception to production.
Responsibilities
Design, build, and maintain scalable, reliable, and secure services that form the backbone of SoFi's ML Platform.
Develop frameworks and tooling for feature generation, model training pipelines, batch and online inference, and real-time monitoring.
Collaborate with Data Science, Risk, and Product teams to understand requirements and translate them into robust technical solutions.
Participate in shaping the long-term technical architecture and platform vision for ML at SoFi.
Drive operational excellence by ensuring services are observable, resilient, and cost-efficient.
Other
Commitment to operational excellence, with experience in observability and monitoring (e.g., DataDog).
Experience collaborating in agile teams with Git, code reviews, and CI/CD pipelines.
Commitment to mentoring engineers and contributing to technical culture.
Bachelor's Degree, ideally in a technical field, but we understand great engineers come from all sorts of different backgrounds and also consider relevant work experience.
