- Страна
- США
- Зарплата
- 138 905 $ – 285 982 $
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Machine Learning Engineer, Core Engineering
Высокая оценка обусловлена сильным брендом компании, конкурентной заработной платой и возможностью работать с уникальными масштабными данными. Pinterest предлагает гибкий формат работы и современную инженерную культуру.
Сложность вакансии
Роль требует серьезного опыта в области рекомендательных систем и обработки больших данных (Spark/Hadoop). Высокая планка ожиданий подкрепляется необходимостью владения современными AI-инструментами разработки и глубоким пониманием архитектур глубокого обучения.
Анализ зарплаты
Предлагаемый диапазон ($139k – $286k) полностью соответствует рыночным стандартам для ML-инженеров уровня Middle/Senior в технологических хабах США. Верхняя граница диапазона является весьма привлекательной даже для топовых компаний Кремниевой долины.
Сопроводительное письмо
I am writing to express my interest in the Machine Learning Engineer position within the Core Engineering team at Pinterest. With over two years of experience in developing large-scale recommendation systems and a deep understanding of deep learning architectures, I am excited by the opportunity to leverage Pinterest's unique dataset of 300 billion ideas to enhance user personalization across Homefeed and Search.
In my previous roles, I have successfully built end-to-end data processing pipelines using Spark and implemented advanced retrieval models that significantly improved candidate generation. I am particularly impressed by Pinterest's forward-thinking approach to AI collaboration and am proficient in using AI-powered tools like Copilot and Cursor to accelerate development workflows. I look forward to the possibility of contributing to your high-impact environment and helping Pinners find the inspiration they love.
Составьте идеальное письмо к вакансии с ИИ-агентом

Откликнитесь в pinterest уже сейчас
Присоединяйтесь к команде Pinterest и создавайте персонализированный опыт для 500 миллионов пользователей по всему миру!
Описание вакансии
About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 3,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.
What you’ll do:
- Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
- Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
- Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
- Work in a high-impact environment with quick experimentation and product launches
- Keeping up with industry trends in recommendation systems
What we’re looking for:
- 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
- End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
- Degree in computer science, machine learning, statistics, or related field
- Nice to have:
+ M.S. or PhD in Machine Learning or related areas
+ Publications at top ML conferences
+ Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
+ Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
+ Expertise in scalable realtime systems that process stream data
+ Passion for applied ML and the Pinterest product
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
#LI-SA1
#LI-REMOTE
At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
US based applicants only
$138,905—$285,982 USD
Our Commitment to Inclusion:
Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.
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Навыки
- Machine Learning
- Deep Learning
- Recommendation Systems
- Spark
- Hadoop
- Python
- SQL
- Natural Language Processing
- Reinforcement Learning
- Graph Learning
- Big Data
- Copilot
- Cursor
Возможные вопросы на собеседовании
Pinterest делает упор на персонализацию. Важно понимать, как кандидат подходит к задаче отбора кандидатов из миллиардов объектов.
Как бы вы спроектировали систему многоэтапного отбора (retrieval) для ленты рекомендаций при наличии сотен миллионов активных пользователей?
В описании указано использование Spark/Hadoop. Вопрос проверяет практический опыт работы с масштабируемыми данными.
Расскажите о самом сложном конвейере обработки данных (data pipeline), который вы оптимизировали. С какими узкими местами вы столкнулись?
Компания активно внедряет AI в процесс разработки. Важно понять, как кандидат использует эти инструменты.
Как вы используете AI-ассистенты (например, Copilot или Cursor) в своем ежедневном рабочем процессе для повышения эффективности кодинга или отладки?
Вакансия предполагает работу над Homefeed, Ads и Search. Вопрос на понимание специфики разных доменов.
В чем, по вашему мнению, основные различия в функциях потерь (loss functions) при обучении моделей для поисковой выдачи и для рекламных рекомендаций?
Pinterest ценит умение объяснять свой подход. Вопрос проверяет способность анализировать результаты экспериментов.
Опишите случай, когда ваша ML-модель показала плохие результаты в продакшене, несмотря на хорошие метрики при офлайн-тестировании. Как вы диагностировали и решили проблему?
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- Страна
- США
- Зарплата
- 138 905 $ – 285 982 $