Machine Learning Engineer, Stripe Assistant at Stripe

This role is designed for a Senior Machine Learning Engineer with at least 5 years of experience who is deeply immersed in the LLM ecosystem. The ideal candidat

Work type: remote

Location: Seattle; San Francisco; New York City; Remote

Salary: $212,000 – $318,000/yr

Type: Full-time

Summary

This role is designed for a Senior Machine Learning Engineer with at least 5 years of experience who is deeply immersed in the LLM ecosystem. The ideal candidate has moved beyond simple API calls and into the world of agentic systems, RAG optimization, and fine-tuning. You should be someone who enjoys the intersection of cutting-edge AI research and robust backend engineering, capable of building "write" actions that are as safe and auditable as they are intelligent. Working on the Stripe Assistant team offers the rare chance to build an AI "operating layer" for global financial infrastructure. While the salary isn't disclosed, the role offers high-impact remote flexibility (including US-wide options) and the opportunity to lead technical strategy for a product evolving from a support chatbot into a proactive business agent. You’ll be setting the SLOs and architectural standards that other internal teams will use to build their own AI agents. **You might be a good fit if you...** * Have hands-on experience with RAG, function calling, agentic orchestration, and RLHF. * Are proficient in Python and comfortable working within complex distributed systems. * Can balance rapid product experimentation with the rigorous security requirements of a financial platform. * Enjoy mentoring other engineers and acting as a technical lead for cross-functional initiatives.

Job Description

## Who we are

### About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

### About the team

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.

## What you’ll do

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.

### Responsibilities

Our team operates fluidly and here are some problems you may tackle:

• 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.

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

### Minimum requirements

• 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.

• Experience operating ML systems at global scale with stringent SLOs—balancing reliability, latency, and cost—with privacy, security, and compliance by design.

• Experience building products where AI/ML is core; as well as balancing short-term product priorities with long-term AI/ML improvements.

• Track record building ML platforms, especially those that enable multiple teams to collaborate together.

• Strong technical leadership and communication: mentoring and elevating engineers, elevating AI/ML awareness and posture within organizations, setting architectural direction, and driving alignment in ambiguity.

View this job on nocollar jobs