Senior Software Engineer, ML Platform
at SoFi
CA - San Francisco, WA - Seattle
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Who we are:
Shape a brighter financial future with us.
Together with our members, we’re changing the way people think about and interact with personal finance.
We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
The role:
At SoFi, our mission is to help people achieve financial independence and realize their ambitions. Within FROST (Fraud, Risk, Operations & Support Technology), we are seeking a Senior Software Engineer to join the Machine Learning Platform team. This team’s charter is to build an enterprise-grade ML platform that not only powers SoFi’s fraud detection and risk mitigation use cases, but also provides scalable, self-serve capabilities that can be leveraged by teams across the company.
The landscape of artificial intelligence and machine learning is evolving rapidly, and SoFi is at the forefront of applying these technologies to protect our members and enable smarter financial services. Our ML Platform team plays a critical role in accelerating model development, deployment, and monitoring, empowering data scientists and engineers to innovate with speed while ensuring compliance, scalability, and reliability.
As a Senior Software Engineer on the ML Platform team, you will help design and build the foundation for SoFi’s ML ecosystem. You will develop services, frameworks, and tooling that support the entire ML lifecycle, from feature generation to training pipelines, batch and online inference, CI/CD integration, and monitoring. While the team focused on Fraud use cases, your work will have company-wide impact, enabling ML-driven capabilities across diverse product areas.
If you are passionate about building high-scale platforms, thrive on technical challenges, and want to work at the intersection of ML, fraud prevention, and financial technology, we encourage you to apply.
What you’ll do:
- 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.
- Contribute to and enforce engineering best practices including CI/CD, testing, and code quality.
- Mentor and support junior engineers, helping foster a culture of growth, innovation, and accountability.
- Proactively generate ideas for new capabilities and improvements to empower SoFi’s ML practitioners.
What you’ll need:
- 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.
- 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.
- Experience collaborating in agile teams with Git, code reviews, and CI/CD pipelines.
- Commitment to operational excellence, with experience in observability and monitoring (e.g., DataDog).
Nice to have:
- Experience with ML frameworks and/or feature platforms (SageMaker, Flink, Spark, TensorFlow, PyTorch, etc.).
- Strong proficiency in Java and/or Kotlin.
- Experience scaling highly available, mission-critical systems.
- Familiarity with fraud detection, risk management, or financial services domains.
- Experience mentoring engineers and contributing to technical culture.
- Interest in personal finance and helping people achieve financial independence.