- Страна
- США
Откликайтесь
на вакансии с ИИ

Machine Learning Engineer, Stripe Assistant
Stripe — один из лучших работодателей в мире технологий с уникальными задачами на стыке финтеха и AI. Позиция предлагает работу над передовыми технологиями (LLM-агенты) и возможность напрямую влиять на продукт мирового уровня.
Сложность вакансии
Роль требует глубоких знаний в области LLM (RAG, агенты, fine-tuning) и опыта построения высоконагруженных распределенных систем. Высокая планка ответственности за архитектуру 'high-trust' действий и лидерские качества делают позицию крайне сложной.
Анализ зарплаты
Учитывая уровень Senior и локации (SF, NYC, Seattle), рыночная зарплата для Stripe находится в верхнем дециле. Ожидаемый совокупный доход (TC), включая опционы, значительно превышает средние показатели по рынку для обычных ML-инженеров.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Machine Learning Engineer position for the Stripe Assistant team. With over five years of experience in AI/ML and backend engineering, I have developed a deep expertise in building agentic systems, optimizing RAG pipelines, and fine-tuning LLMs to solve complex, real-world problems. My background in distributed systems and my passion for creating reliable, high-trust AI products align perfectly with Stripe’s mission to increase the GDP of the internet.
In my previous roles, I have successfully led technical initiatives to improve model performance through RLHF and synthetic data generation, while maintaining rigorous SLOs for latency and cost. I am particularly drawn to this role because of the opportunity to evolve Stripe Assistant from a support tool into a proactive pilot that executes high-trust actions. I am confident that my technical leadership and experience in building scalable ML platforms will allow me to make a significant contribution to your team and help merchants manage their financial infrastructure more efficiently.
Составьте идеальное письмо к вакансии с ИИ-агентом

Откликнитесь в stripe уже сейчас
Присоединяйтесь к Stripe, чтобы создавать будущее финансовых AI-агентов и определять стандарты взаимодействия бизнеса с технологиями.
Описание вакансии
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.
Who you are
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.
Preferred qualifications
- 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.
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.
Создайте идеальное резюме с помощью ИИ-агента

Навыки
- Python
- Machine Learning
- LLM
- RAG
- Prompt Engineering
- Ruby
- Backend Development
- Distributed Systems
- Embeddings
- Reinforcement Learning from Human Feedback
Возможные вопросы на собеседовании
Проверка опыта работы с современными LLM-архитектурами и понимания их ограничений.
Расскажите о вашем опыте проектирования агентных систем: как вы решали проблему зацикливания или некорректного планирования шагов агентом?
Stripe Assistant выполняет финансовые операции, где цена ошибки велика.
Как бы вы спроектировали систему 'human-in-the-loop' для подтверждения критических действий, выполняемых AI-агентом?
Важная часть работы — оптимизация RAG.
Какие стратегии вы использовали для улучшения качества поиска (retrieval) в RAG-системах при работе с узкоспециализированными доменами данных?
Вакансия подразумевает работу с глобальными масштабами.
Как вы подходите к балансировке между качеством ответов модели (accuracy) и задержкой (latency) в продуктовых ML-системах?
Оценка лидерских качеств и умения работать в команде.
Опишите случай, когда вам приходилось убеждать кросс-функциональную команду принять сложное архитектурное решение в условиях неопределенности.
Похожие вакансии
AI Engineer (CV & Navigation)
Senior / Lead LLM Engineer
Middle, Middle+, Senior GenAI/LLM Разработчик
Senior Python AI Developer
GenAI/LLM Разработчик
Middle / Senior GenAI Engineer (CV)
1000+ офферов получено
Устали искать работу? Мы найдём её за вас
Quick Offer улучшит ваше резюме, подберёт лучшие вакансии и откликнется за вас. Результат — в 3 раза больше приглашений на собеседования и никакой рутины!
- Страна
- США