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Machine Learning Engineer (Remote)
Оценка ИИОтличная вакансия в технологически продвинутой компании с сильной инженерной культурой. Привлекательные бонусы, удаленный формат работы и возможность работать с по-настоящему большими данными (Big Data) делают это предложение крайне интересным для ML-специалистов.
Сложность вакансии
Оценка ИИВысокая сложность обусловлена требованиями к глубоким знаниям алгоритмов, структур данных и параллелизма в условиях сверхнизкой задержки (low latency). Работа с распределенными системами и огромными объемами данных требует серьезной математической подготовки и опыта в системном дизайне.
Анализ зарплаты
Оценка ИИЗарплата в объявлении не указана, но StackAdapt позиционирует её как 'высококонкурентную'. Для рынка Северной Америки (США/Канада) в сфере AdTech уровни компенсации для ML-инженеров обычно находятся в верхнем дециле рынка из-за высокой сложности задач.
Сопроводительное письмо
I am writing to express my strong interest in the Machine Learning Engineer position at StackAdapt. With a solid background in computer science and experience in implementing machine learning algorithms within low-latency environments, I am excited by the prospect of contributing to a platform that processes 465 billion automated optimizations per second. My expertise in designing scalable distributed systems and microservice architectures aligns perfectly with your team's mission to build robust ad optimization models.
Throughout my career, I have focused on breaking down ambiguous tasks into actionable steps and developing modular data pipelines for massive datasets. I am particularly impressed by StackAdapt's remote-first culture and its commitment to innovation in the programmatic advertising space. I look forward to the possibility of bringing my technical skills and collaborative mindset to your Data Science team to help drive measurable results across the customer journey.
Составьте идеальное письмо к вакансии с ИИ-агентом
Откликнитесь в stackadapt уже сейчас
Присоединяйтесь к команде StackAdapt и создавайте ML-решения для обработки миллионов запросов в секунду!
Описание вакансии
StackAdapt is the leading technology company that empowers marketers to reach, engage, and convert audiences with precision. With 465 billion automated optimizations per second, the AI-powered StackAdapt Marketing Platform seamlessly connects brand and performance marketing to drive measurable results across the entire customer journey. The most forward-thinking marketers choose StackAdapt to orchestrate high-impact campaigns across programmatic advertising and marketing channels.
We're looking to add a Machine Learning Engineer to our Data Science team! This team works on solving complex problems for StackAdapt's digital advertising platform. You'll be working directly with our Data Scientists, Machine Learning Engineers, Engineering teams, and our CTO/Co-Founder on building pipelines and ad optimization models. With databases that process millions of requests per second, there's no shortage of data and problems to tackle.
StackAdapt is a remote-first company with teams around the world. Our teams work in a fully distributed environment, and we are open to candidates based in Canada and the United States.
This role will remain open until February 20, 2026. Applications will be reviewed on a rolling basis, and the posting will close once the deadline is reached.
Want to learn more about our Data Science Team: https://alldus.com/ie/blog/podcasts/aiinaction-ned-dimitrov-stackadapt/
Learn more about our team culture here: https://www.stackadapt.com/careers/data-science
Watch our talk at Amazon Tech Talks: https://www.youtube.com/watch?v=lRqu-a4gPuU
What you'll be doing:
- Design modular and scalable real time data pipelines to handle huge datasets
- Understand and implement custom ML algorithms in a low latency environment
- Work on microservice architectures that run training, inference, and monitoring on thousands of ML models concurrently
What you'll bring to the table:
- Have the ability to take an ambiguously defined task, and break it down into actionable steps
- Have deep understanding of algorithm and software design, concurrency, and data structures
- Experience in implementing probabilistic or machine learning algorithms
- Interest in designing scalable distributed systems
- A high GPA from a well-respected Computer Science program
- Enjoy working in a friendly, collaborative environment with others
StackAdapter's Enjoy:
- Highly competitive salary
- Retirement/ 401K/ Pension Savings globally
- Competitive Paid time off packages including birthday's off!
- Access to a comprehensive mental health care program
- Health benefits from day one of employment
- Work from home reimbursements
- Optional global WeWork membership for those who want a change from their home office and hubs in London and Toronto
- Robust training and onboarding program
- Coverage and support of personal development initiatives (conferences, courses, books etc)
- Access to StackAdapt programmatic courses and certifications to support continuous learning
- An awesome parental leave program
- A friendly, welcoming, and supportive culture
- Our social and team events!
StackAdapt is a diverse and inclusive team of collaborative, hardworking individuals trying to make a dent in the universe. No matter who you are, where you are from, who you love, follow in faith, disability (or superpower) status, ethnicity, or the gender you identify with (if you’re comfortable, let us know your pronouns), you are welcome at StackAdapt. If you have any requests or requirements to support you throughout any part of the interview process, please let our Talent team know.
We use artificial intelligence (AI) to streamline the resume reviews of candidates and assess their fit based on the criteria outlined in the job posting. We do not use AI to make any final hiring or interview decisions.
About StackAdapt
We've been recognized for our diverse and supportive workplace, high performing campaigns, award-winning customer service, and innovation. We've been awarded:
Ad Age Best Places to Work 2024
G2 Top Software and Top Marketing and Advertising Product for 2024
Campaign’s Best Places to Work 2023 for the UK
2024 Best Workplaces for Women and in Canada by Great Place to Work®
#1 DSP on G2 and leader in a number of categories including Cross-Channel Advertising
To learn more about our privacy practices, please see our Privacy Policy.
#LI-REMOTE
Создайте идеальное резюме с помощью ИИ-агента
Навыки
- Machine Learning
- Distributed Systems Architecture
- Microservices
- Concurrency
- Data Structures
- Algorithms
- Data Pipelines
- Low Latency
Возможные вопросы на собеседовании
Учитывая специфику StackAdapt (миллионы запросов в секунду), важно понимать, как кандидат оптимизирует код для работы в реальном времени.
Как бы вы спроектировали ML-модель для инференса с задержкой менее 10 мс при обработке огромного потока данных?
Вакансия требует навыков проектирования масштабируемых систем.
Опишите ваш опыт работы с микросервисной архитектурой для одновременного обучения и мониторинга тысяч моделей.
В описании упоминается работа с неопределенными задачами.
Приведите пример, когда вы превратили абстрактную бизнес-задачу в конкретный технический план реализации ML-решения.
Компания работает с вероятностными алгоритмами.
В каких случаях вы бы предпочли вероятностный подход классическому детерминированному алгоритму в контексте рекламных технологий?
Проверка фундаментальных знаний, на которые делается упор в вакансии (высокий GPA, знание структур данных).
Как вы подходите к оптимизации использования памяти и ресурсов CPU при обработке распределенных наборов данных?
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