Senior Machine Learning Engineer
About this role
About Bluevine
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?
About the role
At Bluevine, we’re on a mission to empower small businesses with innovative financial solutions. In this role, you will take an integral part in designing the next-generation infrastructure that powers our data-driven products. You will help shape and build the platforms and production-grade solutions that enable our Data teams to deliver impactful AI/ML capabilities at scale. If you are passionate about turning complex data into reliable, scalable systems that solve real-world financial challenges, we want you on our team.
What You'll Do
- Build AI/ML Infrastructure: Design, develop, and maintain platforms and tooling that accelerate the entire AI lifecycle—from experimentation and training to deployment, observability, and governance.
- Productionize AI: Partner with our Data Science, Analytics, and Research teams to turn prototypes and notebooks into highly reliable, scalable production systems.
- Develop Modern AI Workflows: Build robust data and feature pipelines, and develop reusable components for GenAI capabilities like LLMs, embeddings, RAG, and agentic workflows.
- Champion Best Practices: Utilize orchestration tools, cloud AI services (such as AWS Bedrock, SageMaker, etc.), and modern frameworks to design first-in-class solutions for the financial sector.
What We Look For
- 5+ years of full-time Software Engineering experience in a fast-paced, data-centric environment, with strong proficiency in Python.
- 2+ years of hands-on experience in a Machine Learning Engineering, MLOps, ML Infrastructure, or hands-on, full-stack Data Science role.
- Deep understanding of the entire ML/DS lifecycle, from research and development to deployment.
- Proven hands-on experience in building production-grade solutions, platforms, or infrastructure for AI or ML.
- Experience building and deploying modern AI and LLM-based systems (prompt orchestration, embeddings, retrieval-augmented generation, and evaluation frameworks).
- Deep experience with cloud infrastructure (AWS preferred), including services like SageMaker, Bedrock, Lambda, and S3.
- Strong software engineering fundamentals, including system design, CI/CD, testing, code quality, and operational excellence.
- Exceptional communication skills, with the ability to collaborate smoothly and explain complex technical ideas clearly.
- Proactive, result-driven team player with very good English (written and verbal).
Bonus points if you also have:
- Experience with vector databases, advanced experiment tracking tools, or specialized ML observability platforms.
- Background in streaming, event-driven systems, and real-time analytics.
- Experience with responsible AI, model risk management, explainability, or bias testing in regulated industries.
- Experience in fintech, banking, lending, risk, fraud, or financial data systems.
Benefits & Perks
- Excellent group health coverage
- Stock options
- Flexible hybrid work model
- Large Study Fund contribution
- Salary Benchmarks and Checkpoints
- Monthly meal card of TenBis or CiBus (your choice) with generous balance
- Free parking for cars, scooters, and bikes
- Free gym membership
- Company-sponsored Mental Health Benefits
- PTO, Company Holidays, and Flexible Holidays
- Community-based volunteering opportunities
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