Machine Learning Engineer, Stripe

• 5+ years in AI/ML and backend engineering
• Applied LLM experience: RAG/embeddings, tool use/function calling, agentic planning/orchestration, fine-tuning, code generation, evaluations, etc
• Proficient in Python (Ruby is a plus); strong distributed systems fundamentals
• Experience working closely with product management, design, other engineers, and other cross-functional partners
• At Stripe, we're looking for people with passion, grit, and integrity. You're encouraged to apply even if your experience doesn't precisely match the job description. Your skills and passion will stand out—and set you apart—especially if your career has taken some extraordinary twists and turns

Desirable

• The Stripe Assistant team is transforming how users interact with Stripe by building an intelligent and proactive assistant that not only answers users’ queries but efficiently resolves issues and provides valuable business insights
• We leverage LLMs and agentic systems to elevate the user experience across Stripe—from the dashboard to support surfaces—and we enable other teams to build and integrate their AI agents on our platform
• We’re evolving from a helpful support tool to a trusted pilot that anticipates, optimizes, and executes on behalf of our users
• As a Senior Machine Learning Engineer on the Stripe Assistant team, you’ll own the end-to-end ML and agent architecture that makes Stripe Assistant safe, reliable, and deeply useful
• You’ll set the strategy for how the Assistant executes high-trust actions, delivers accurate analytical answers across Stripe and the broader web, orchestrates capabilities across many tools and agents, and grounds responses in authoritative Stripe and user data—so users can resolve issues quickly and confidently
• You’ll drive conversation continuity and personalization across surfaces, evolve the Assistant into a proactive partner that anticipates user needs, and deepen its presence in the dashboard to streamline critical workflows
• You’ll establish rigorous evaluation and SLOs and deliver step‑change improvements in quality, latency, cost, and availability—paving the way for configurable levels of autonomy and, ultimately, a dependable operating layer over a merchant’s Stripe account
• Establish trustworthy, human-in-the-loop execution for high-trust “write” actions—prioritizing user control, transparency, accountability, and auditability so customers can delegate with confidence
• Define and evolve the Assistant’s capability and governance model across hundreds of tools and agents, balancing power, permissions, and consistency at scale
• Raise answer quality and usefulness by grounding in authoritative Stripe knowledge and live user data, building cross-surface memory and personalization, and making the Assistant proactive and present in the dashboard
• Explore and apply optimal machine learning methods to improve Stripe Assistant’s overall performance, including but not limited to fine-tuning LLMs with RLHF, synthetic data generation, optimizing RAG pipelines via domain‑specific embedding and retriever fine‑tuning, and automatic prompt tuning, etc
• Make quality and reliability a product: set and meet SLOs, build rigorous evaluation and benchmarking loops, and drive sustained improvements in latency, cost, and availability
• Lead as a tech lead: mentor and grow engineers, uphold high bars for code quality, security, observability, and operational rigor, and align cross‑functionally to ship safely and fast
• Join us to build a trustworthy, proactive AI operating layer for every Stripe merchant—advancing safety, reliability, and insight at global scale. If you’re ready to help take Stripe Assistant from copilot to full autopilot and shape how businesses connect with Stripe, we’d love to hear from you