Staff Machine Learning Engineer

Innovate with purpose

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 By replacing outdated financial processes with innovative tools, we help businesses—from startups to established brands—make smarter decisions and gain control of their operations.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. We're remote-first, with office spaces in San Jose, CA and Draper, UT — and opportunities to connect in person when it counts. 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.

Make your impact at a leading Fintech Company

Join BILL's AI Product Engineering team and help shape the future of intelligent financial automation. BILL processes millions of financial documents every month, and machine learning sits at the core of how we turn unstructured documents into accurate, actionable financial data. We are looking for a Staff ML Engineer to raise the technical bar across our AI/ML organization, someone who is equally comfortable getting hands-on with model training code and setting the multi-quarter technical direction for a team.

This is a senior individual-contributor role with organization-wide influence. You will architect and build the next generation of our ML systems, spanning LLM-based extraction, fine-tuned open-weight models, intelligent routing, and the data foundations underneath them, while mentoring engineers and shaping how we evaluate, deploy, and iterate on models in production.

• Own technical direction for high-impact ML initiatives end to end, from problem framing and research exploration through production deployment and measurement, across document understanding, field extraction, and model-serving infrastructure

• Stay hands-on: prototype, fine-tune, and ship models yourself; write production code alongside the engineers you mentor

• Lead our LLM strategy, including fine-tuning open-weight foundation models, designing evaluation harnesses, and making principled build-vs-buy decisions between self-hosted and frontier API models across accuracy, cost, latency, and privacy constraints

• Bring a research-oriented mindset to production problems: read and translate current literature into practice, design rigorous experiments and ablations, and know when a published technique will or won't transfer to our data distribution

• Design the data flywheel, including labeling pipelines, human-in-the-loop feedback, and drift monitoring, so our models improve continuously from production signals

• Set engineering standards for model evaluation, calibration, reproducibility, and responsible deployment; be the person others seek out for design reviews on anything ML-shaped

• Mentor and multiply: grow senior and mid-level ML engineers through code review, pairing, and technical guidance; influence roadmaps in partnership with product and platform leadership

• Requires a minimum of 8 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or a