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Engineering Manager, Machine Learning Platform
Оценка ИИStripe — один из самых престижных работодателей в мире технологий с уникальными данными и инженерной культурой. Позиция предлагает исключительное влияние на продукт и возможность работать над задачами мирового масштаба в Торонто.
Сложность вакансии
Оценка ИИРоль требует редкого сочетания 10-летнего инженерного опыта и глубокой экспертизы в ML-инфраструктуре. Управление распределенными командами и работа с системами сверхвысокой нагрузки (1.9 трлн долларов в платежах) значительно повышают планку ответственности.
Анализ зарплаты
Оценка ИИЗарплата в Stripe для уровня Engineering Manager в Торонто обычно находится на верхней границе рынка, часто превышая средние показатели за счет значительного пакета акций (RSU). Указанный рыночный диапазон отражает общие цифры для BigTech в Канаде.
Сопроводительное письмо
I am writing to express my strong interest in the Engineering Manager position for the ML Platform team at Stripe. With over a decade of experience in software development and a proven track record of managing high-performing engineering teams, I have consistently focused on building scalable, low-latency systems that solve complex data challenges. My background in leading cross-functional initiatives aligns perfectly with Stripe's mission to increase the GDP of the internet through robust financial infrastructure.
In my previous roles, I have successfully overseen the development of large-scale data foundations and serving layers, ensuring high availability and performance for machine learning models in production. I am particularly drawn to Stripe's unique position in the industry, where the sheer volume of data provides an unparalleled environment for ML innovation. I am eager to bring my expertise in fostering inclusive work environments and driving technical roadmaps to help shape the next generation of ML Serving and observability at Stripe.
Составьте идеальное письмо к вакансии с ИИ-агентом
Откликнитесь в stripe уже сейчас
Присоединяйтесь к Stripe, чтобы возглавить разработку ML-инфраструктуры мирового масштаба и влиять на 1.6% мирового ВВП.
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
Stripe processes over $1.9 T in payments volume per year, which is roughly 1.6% of the world's GDP, for millions of customers from startups to enterprises. The tremendous amount of data makes Stripe one of the best places to do machine learning. While being an integral part of almost every product line at Stripe (e.g., Payments, Radar, Capital, Billing, etc.), we have lots of exciting opportunities to innovate in ML Platform at Stripe.
The ML Platform team builds the platforms and services that enable ML engineers and data scientists across Stripe to take the data and build features and models from prototype to production — reliably, at low latency, and at scale. We work closely with product teams, data scientists, and platform infrastructure teams to build powerful, flexible, and user-friendly systems that substantially increase ML velocity across the company.
What you’ll do
You will have the opportunity to shape the future of ML Data Foundations platform, ML Serving and observability at Stripe. You will help define the long-term strategy and lead the team in building the next generation of serving infrastructure that powers most if not all of Stripe's ML-driven products.
Responsibilities
- Hire, lead and manage a team of talented engineers on the team, providing mentorship, guidance, and support to ensure their success.
- Collaborate with cross-functional teams, including senior leadership, ML Platform teams, data platform, data science, machine learning, and other business orgs to understand user needs and translate them into technical solutions.
- Define the vision and roadmap aligning it with business objectives and industry best practices.
- Drive the execution of projects, overseeing the entire development lifecycle from planning to delivery, while maintaining high standards of quality and timely completion.
- Foster a collaborative and inclusive work environment, promoting innovation, knowledge sharing, and continuous improvement within the team.
- Stay up-to-date with emerging technologies, industry trends, and advancements in AI/ML to identify opportunities for innovation and improvement.
- Communicate effectively with stakeholders, providing regular updates on project status, progress, and any potential risks or challenges.
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
- 10+ years of software development experience and 3+ years of engineering management experience building user-centric products
- Proven track record of building and operating large scale, highly available, low-latency systems
- Experience working in highly cross-functional organizations
- The ability to thrive on a high level of autonomy and responsibility
- The desire to encourage a healthy, inclusive work environment that's both supportive and challenging
- Clear and persuasive writing and in-person communication
Preferred qualifications
- Experience in building large-scale serving or data infrastructure for machine learning use cases (e.g., model inference, feature stores, real-time feature computation)
- Familiarity with cloud services (e.g., AWS) and cloud-based AI/ML services (e.g., SageMaker, Bedrock, Databricks, OpenAI, etc.)
- Comfortable working with geographically distributed teams
- Experience with applying machine learning to real-world problems
Создайте идеальное резюме с помощью ИИ-агента
Навыки
- Machine Learning
- Distributed Systems Architecture
- ML Infrastructure
- Scalability Architecture
- Engineering Management Architecture
- AWS Architecture
- Python Architecture
- Data Infrastructure Architecture
- MLOps Architecture
Возможные вопросы на собеседовании
Проверка опыта управления в условиях высокой ответственности и масштаба Stripe.
Расскажите о самом сложном техническом проекте под вашим руководством: как вы балансировали между скоростью доставки и надежностью системы?
Оценка способности кандидата выстраивать отношения с пользователями платформы (ML-инженерами).
Как вы определяете приоритеты в дорожной карте ML-платформы, когда запросы от продуктовых команд и дата-сайентистов противоречат друг другу?
Проверка понимания специфики ML-инфраструктуры.
Какие ключевые метрики вы бы внедрили для оценки эффективности системы обслуживания моделей (ML Serving) и Feature Store?
Оценка лидерских качеств и умения развивать таланты.
Опишите ваш подход к менторству старших инженеров и как вы помогаете им расти внутри организации.
Проверка навыков кризис-менеджмента в критически важных системах.
Был ли у вас опыт устранения масштабных сбоев в высоконагруженных системах? Какова была ваша роль как менеджера в этом процессе?
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