TL;DR

Senior Staff Machine Learning Engineer (Fintech): Architecting and overseeing the design of end-to-end ML systems, owning the operational roadmap for production-level inference, fine-tuning, and LLM orchestration at a large scale. Focus on driving innovation and research, scaling the data backbone, and shaping strategy and goals within the engineering organization.

Location: Must be based in the US

Salary: $216,000 - $269,900 USD

Company

BILL helps businesses make smarter decisions and gain control of their operations by replacing outdated financial processes with innovative tools.

What you will do

  • Lead the architectural strategy and design for end-to-end ML systems, owning the operational roadmap for production-level inference, fine-tuning, and LLM orchestration at a large scale.
  • Develop and standardize reusable ML modeling frameworks, high-performance data pipelines, and internal libraries.
  • Lead applied research initiatives, designing experiments that push the boundaries of Bill's AI capabilities.
  • Oversee the evolution of Bill's data infrastructure, ensuring ETL processes and structured datasets are built for maximum scalability and long-term maintainability.
  • Identify emerging AI opportunities and transform them into core business goals, influencing the broader engineering organization's AI roadmap.
  • Define and enforce best practices for ML engineering, partnering with leadership to mentor junior engineers and ensure the team is operating at peak technical excellence.

Requirements

  • 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.
  • Deep expertise in building backend systems that support AI-driven products, specifically focusing on the scalability and maintainability of LLM-based architectures.
  • Expert-level experience in building complex data pipelines (ETL, cleaning, structuring) that serve as the foundation for high-performing, mission-critical AI systems.
  • Ability to bridge the gap between theoretical ML research and production engineering, with a focus on measurable data-driven outcomes.
  • Strong communication skills with a history of shaping team goals, defining engineering standards, and raising the technical profile of the teams you work with.
  • Experience managing the risks and trade-offs of complex AI deployments, including performance optimization and cost-effective scaling.

Culture & Benefits

  • 100% paid employee health, dental, and vision plans (choose HMO, PPO, or HDHP)
  • HSA & FSA accounts
  • Employee Stock Purchase Program with employee discounts
  • Wellness & Fitness initiatives
  • Employee recognition and referral programs