- Страна
- Канада
Откликайтесь
на вакансии с ИИ
Applied Machine Learning Scientist (Remote)
Оценка ИИОтличная вакансия в технологическом лидере индустрии AdTech с удаленным форматом работы, сильной инженерной культурой и расширенным пакетом льгот.
Сложность вакансии
Оценка ИИВысокая сложность обусловлена требованиями к ученой степени (Masters/PhD), глубоким знаниям в оптимизации и статистике, а также необходимости писать промышленный код для высоконагруженных систем.
Анализ зарплаты
Оценка ИИЗарплата в объявлении не указана, но для позиций Applied ML Scientist в Северной Америке (США/Канада) рыночные показатели значительно выше средних по IT-сектору из-за высокой наукоемкости роли. Продуктовые компании уровня StackAdapt обычно предлагают конкурентоспособные пакеты, включающие опционы и бонусы.
Сопроводительное письмо
I am writing to express my strong interest in the Applied Machine Learning Scientist position at StackAdapt. With a solid background in developing innovative ML algorithms and a passion for high-scale programmatic advertising, I am drawn to StackAdapt’s impressive capability of handling 465 billion automated optimizations per second. My experience in bridging the gap between academic research and production-ready code aligns perfectly with your mission to drive measurable results across the customer journey.
Throughout my career, I have focused on breaking down ambiguous problems into actionable data science solutions, particularly in the realms of optimization and statistical modeling. I am proficient in writing clean, production-grade code and have a proven track record of prototyping and iterating on algorithms using historical data. I am excited about the prospect of contributing to a Remote First company that values continuous learning and fosters a collaborative, inclusive environment.
Составьте идеальное письмо к вакансии с ИИ-агентом
Откликнитесь в stackadapt уже сейчас
Присоединяйтесь к команде StackAdapt и создавайте алгоритмы машинного обучения, которые обрабатывают миллионы 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 are searching for a talented Applied Machine Learning Scientist to join our engineering team as we continue to expand our data science efforts. Our platform is connected to thousands of publishers and advertisers worldwide and as a result, we're dealing with millions of requests each second, making billions of decisions. We utilize the latest technologies to solve challenges in traffic, data storage, machine learning, and scalability.
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
StackAdapt is a Remote First company, and we are open to candidates located anywhere in North America for this position.
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.
What you'll be doing:
- Innovate ML algorithms to maximize ROI and advertising performance. This ranges from creating entirely new algorithms, to improvements on state-of-the art methods, to development using a deep understanding of classic methods
- Write production code, sometimes collaborating with Data Engineers, to implement the novel ML algorithms
- Prototype potential algorithms and pipelines, test them using historical data, and iterate to modify based on insights
What you'll bring to the table:
- Have a Masters degree or PhD in Computer Science, Statistics, Operations Research, or a related field, with dual degrees a plus.
- Have the ability to take an ambiguously defined task, and break it down into actionable steps
- Have a comprehensive understanding of statistics, optimization and machine learning
- Are proficient in coding, data structures, and algorithms
- 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
- Python
- Statistics
- Algorithms
- Data Structures
- Optimization
- Computer Science
- Research
Возможные вопросы на собеседовании
Проверка способности работать с огромными объемами данных в реальном времени, что критично для DSP-платформ.
Как бы вы спроектировали систему машинного обучения для обработки миллионов запросов в секунду с минимальной задержкой (latency)?
Вакансия требует умения превращать неопределенные задачи в конкретные шаги.
Расскажите о случае, когда вам дали абстрактную бизнес-задачу. Как вы формализовали её в терминах ML и какие метрики выбрали?
В описании упоминается инновация алгоритмов для максимизации ROI.
Какие методы оптимизации вы бы использовали для балансировки между стоимостью показа рекламы и вероятностью конверсии?
Роль предполагает написание продакшн-кода и сотрудничество с инженерами данных.
Каков ваш опыт внедрения ML-моделей в эксплуатацию? Как вы обеспечиваете воспроизводимость и мониторинг качества моделей?
Проверка фундаментальных знаний, необходимых для улучшения state-of-the-art методов.
В чем заключаются основные математические различия между классическими методами регрессии и современными глубокими нейросетями в контексте предсказания CTR?
Похожие вакансии
Senior Data инженер
Senior MLOps Engineer (Platform Development / LLMOps)
Data Engineer / SAP HANA Developer (Senior)
Data Engineering Team Lead (команда Clickhouse)
Senior ML Engineer
Senior MLOps
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
- Канада