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PhD Machine Learning Engineer, Intern
Оценка ИИЭто исключительная возможность для PhD-студентов поработать в одной из самых технологичных компаний мира над реальными задачами мирового масштаба с использованием передового стека (LLM, Foundation Models).
Сложность вакансии
Оценка ИИВысокая сложность обусловлена требованием статуса PhD в области Computer Science или ML, а также необходимостью иметь публикации в топовых изданиях и опыт работы с высоконагруженными системами.
Анализ зарплаты
Оценка ИИStripe предлагает одни из самых высоких компенсаций для интернов уровня PhD в индустрии, часто превышающие средние рыночные показатели для стажировок. Указанный диапазон отражает типичные ставки для топовых финтех-компаний в США.
Сопроводительное письмо
I am writing to express my strong interest in the PhD Machine Learning Engineering Internship at Stripe for Summer 2026. As a PhD candidate specializing in Machine Learning, I have closely followed Stripe’s innovations in financial infrastructure, particularly the development of the Stripe Foundation Model and Stripe Assistant. My research background, combined with my proficiency in Python, Spark, and Scikit-learn, aligns perfectly with your mission to increase the GDP of the internet through advanced applied ML.
During my doctoral studies, I have focused on developing scalable models that solve complex data challenges, much like the fraud detection and user behavior prediction tasks mentioned in the job description. I am particularly drawn to Stripe’s culture of technical excellence and the opportunity to deploy production-scale models that have a tangible impact on millions of businesses. I am eager to bring my expertise in supervised learning and LLMs to your Applied ML team and contribute to the next generation of financial services.
Составьте идеальное письмо к вакансии с ИИ-агентом
Откликнитесь в stripe уже сейчас
Присоединяйтесь к Stripe, чтобы создавать ML-решения, определяющие будущее мировой экономики!
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.
What you’ll do
About the internship
Stripe's Applied ML, Data Science, Risk, and Payments organizations are excited to offer PhD machine learning engineering internships for the summer of 2026. This is an exceptional opportunity to contribute to critical projects that directly enhance Stripe's suite of products, focusing on areas such as foundation models used for dozens of tasks e.g. fraud detection, enhanced support, and predicting user behavior.
As an intern, you'll tackle challenging problems at the intersection of finance, technology, and data. You'll have the chance to work on creative projects like the Stripe Assistant and the Stripe Foundation Model, which leverage machine learning to revolutionize how businesses interact with financial services and data.
Responsibilities
- Develop and deploy large-scale machine learning systems that drive significant business value across various domains.
- Engage in the end-to-end process of designing, training, improving, and launching machine learning models.
- Write production-scale ML models that will be deployed to help Stripe enable economic infrastructure access for a diverse range of businesses globally.
- Collaborate across teams to incorporate feedback and proactively seek solutions to challenges.
- Rapidly learn new technologies and approaches, demonstrating a strong ability to ask insightful questions and communicate the status of your work effectively.
Who you are
Minimum requirements
- A deep understanding of computer science, obtained through the pursuit of a PhD in Computer Science, Machine Learning, or a closely related field, with the expectation of graduating in winter 2026 or spring/summer 2027.
- Practical experience with programming and machine learning, evidenced by projects, classwork, or research. Familiarity with languages such as Python, Scala, Spark and libraries such as Pandas, NumPy, and Scikit-learn.
- Expertise in areas of machine learning such as supervised and unsupervised learning techniques, ML operations, and possibly experience in Large Language Models or Reinforcement Learning.
- Demonstrated ability to work on collaborative projects, with experience in receiving and applying feedback from various stakeholders.
- A proactive approach to learning unfamiliar systems and a demonstrated ability to understand complex systems independently.
- Intent to return to the degree-program after the completion of the internship/co-op.
Preferred qualifications
You Might Also Have:
- Two years of university education or equivalent experience, with in-depth knowledge in specific domains of machine learning.
- Published and presented peer-reviewed articles in top-tier venues.
- Experience in writing high-quality pull requests, maintaining good test coverage, and completing projects with minimal defects.
- Familiarity with navigating new codebases and managing work across different programming languages.
- Excellent written communication skills to clearly articulate your work to both team members and wider Stripe audiences.
Application requirements
Please submit the following with your application:
- A detailed resume or LinkedIn profile showcasing your work history.
- Examples of relevant work and your approach to learning, such as GitHub repositories, StackOverflow contributions, or other project portfolios.
Join us for an unforgettable summer internship and help shape the future of global commerce. At Stripe, you won't just be working on theoretical projects; you'll make a tangible impact on the world's economic infrastructure.
Создайте идеальное резюме с помощью ИИ-агента
Навыки
- Python
- NumPy
- Pandas
- Machine Learning
- Large Language Models
- MLOps
- Scikit-learn
- Apache Spark
- Scala
- Reinforcement Learning
Возможные вопросы на собеседовании
Проверка глубины теоретических знаний, соответствующих уровню PhD.
Расскажите о вашей диссертации или ключевом исследовательском проекте: какую проблему вы решали и каков был ваш вклад в теорию или практику ML?
Stripe работает с огромными объемами данных, важно понимать навыки масштабирования.
Как бы вы спроектировали систему обучения модели на терабайтах данных о транзакциях для обнаружения фрода в реальном времени?
В описании упоминаются LLM и Stripe Assistant.
Какие методы дообучения (fine-tuning) или оптимизации контекста (RAG) вы бы применили для создания финансового ассистента на базе LLM?
Проверка навыков работы с инструментами, указанными в вакансии.
Опишите ваш опыт работы со Spark и Scala: в каких сценариях вы предпочитаете использовать Spark вместо чистого Python/Pandas?
Оценка способности доводить исследования до продакшена.
Расскажите о случае, когда вам пришлось оптимизировать ML-модель для работы в продакшене с жесткими ограничениями по задержке (latency).
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