Senior Staff Machine Learning Engineer

BILL•San Jose, CA

About The Position

At BILL, we believe in empowering the businesses that drive our economy. By replacing outdated financial processes with innovative tools, we help businesses—from startups to established brands—make smarter decisions and gain control of their operations. And we don’t stop there: we’re creating the future of financial automation so businesses can spend more time on what matters. Working here means you become part of a vision-driven team that’s ready to tackle challenges and build cutting-edge solutions. We value purpose, drive, and curiosity—and we thrive in a fast-paced, ever-changing environment. Whether in one of our offices in San Jose, CA, Draper, UT, or in a remote-eligible role, BILLders collaborate to deliver real impact for businesses that need more time in their busy weeks. BILL builds high performing teams and we seek to hire the best talent for every role. We're committed to building a workplace that fosters inclusion and diverse perspectives, valuing each person’s unique skills and experiences. We’d love to hear from you—you might be just what we’re looking for, whether in this role or another. ✨ Let’s give businesses more time for what matters. Come join BILL’s AI Product and Platform team, the group building the intelligence backbone that powers every AI and agent-driven experience across our products. You’ll architect large-scale LLM infrastructure, evaluation, and data systems that hundreds of thousands of customers and every internal developers rely on every day. You’ll partner closely with product and engineer teams to launch new agents, drive down latency and cost, and set the technical standards that raise the bar for AI across the company. Make your impact within a rapidly growing Fintech Company

Requirements

Proven Leadership: A track record of leading complex, high-impact AI projects from ideation to production, with a focus on large-scale distributed systems, cloud infrastructure and operational excellence.
Architectural Mastery: Deep expertise in building backend systems that support AI-driven products, specifically focusing on the scalability and maintainability of LLM-based architectures.
Strategic Data Engineering: Expert-level experience in building complex data pipelines (ETL, cleaning, structuring) that serve as the foundation for high-performing, mission-critical AI systems.
Applied Research Mindset: Ability to bridge the gap between theoretical ML research and production engineering, with a focus on measurable data-driven outcomes.
Influence & Mentorship: Strong communication skills with a history of shaping team goals, defining engineering standards, and raising the technical profile of the teams you work with.
Advanced Problem Solving: Experience managing the risks and trade-offs of complex AI deployments, including performance optimization and cost-effective scaling.

Responsibilities

Architect & Oversee: Lead the architectural strategy and design for end-to-end ML systems. You will own the operational roadmap for production-level inference, fine-tuning, and LLM orchestration at a large scale.
Build Reusable Frameworks: Develop and standardize reusable ML modeling frameworks, high-performance data pipelines, and internal libraries that set the bar for performance, accuracy, and explainability across all engineering teams.
Drive Innovation & Research: Lead applied research initiatives. You will design experiments that push the boundaries of Bill's AI capabilities, turning both successful innovations and "failed" experiments into institutional knowledge.
Scale the "Data Backbone": Oversee the evolution of Bill's data infrastructure, ensuring that ETL processes and structured datasets are built for maximum scalability and long-term maintainability.
Shape Strategy & Goals: Identify emerging AI opportunities and transform them into core business goals. You will influence the broader engineering organization's AI roadmap and manage technical risks across multiple projects.
Raise the Bar: Define and enforce best practices for ML engineering. You will partner with leadership to mentor junior engineers and ensure the team is operating at peak technical excellence.