Senior Machine Learning Engineer

Bluevine is the largest small business banking platform in the U.S., redefining how entrepreneurs manage their money. We create modern financial solutions, from checking and lending to payments and beyond, designed to help small business owners grow, thrive, and take control of their financial future. Our best-in-class technology, advanced security, and deep understanding of the small business community give our customers the confidence to focus on what they do best.

Since 2013, we’ve supported more than 750,000 small businesses nationwide. Backed by leading investors like Lightspeed Venture Partners, Menlo Ventures, 83North, and Citi Ventures, our 500+ person global team shares one mission: to give small businesses the financial tools they need to succeed.

We’re innovators driven by big ideas, collaboration, and real impact. Here, you’ll have the freedom to take ownership, grow your career, and make a difference for small business owners across America. Ready to shape what’s next?

• →Build and maintain platforms and tools that support the development, deployment, and operation of AI solutions.
• →Design data frameworks for complex batch and streaming workflows.
• →Develop validation and monitoring mechanisms to maintain data quality, system reliability, and production performance.
• →Improve the scalability and operational efficiency of data and AI systems.
• →Partner with Data Engineering, Data Science and Analytics teams to translate technical requirements and prototypes into production-ready solutions.
• →Contribute to system design, engineering standards, and technical best practices.

• 5+ years of professional software development experience in backend or infrastructure engineering, with strong proficiency in Python.
• Hands-on experience building and deploying AI / LLM-based systems, including AI workflows, prompt orchestration, or evaluation frameworks.
• Hands-on experience with AWS infrastructure and services such as SageMaker, Bedrock, Lambda, and S3.
• Experience designing reusable frameworks, internal platforms, or shared engineering capabilities.
• Strong knowledge of modern Data Engineering concepts, including distributed computing, batch and streaming processing, feature stores, and data validation.
• Strong software engineering fundamentals, including system design, CI/CD, automated testing, code quality, and production operations.
• Strong communication skills and the ability to collaborate effectively across technical teams.
• Very good written and spoken English.

• Experience with event-driven architectures or real-time analytics.
• Experience in fintech, banking, lending, risk, fraud, or financial data systems.