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Senior Machine Learning Engineer - Applied ML & Research
Оценка ИИОтличная позиция в крупной международной компании с серьезной финансовой поддержкой (Blackstone). Использование современных технологий (LLM, AWS, Kafka) и четкие критерии роста делают вакансию крайне привлекательной для Senior-специалистов.
Сложность вакансии
Оценка ИИРоль требует глубоких знаний в области ML-фундаментала и LLM, а также сильных навыков программной инженерии. Высокая планка обусловлена необходимостью работы с высоконагруженными системами и сложными пайплайнами в сфере онлайн-гейминга.
Анализ зарплаты
Оценка ИИЗарплата в вакансии не указана, но для Senior ML ролей в Нидерландах рынок предлагает конкурентные условия. Учитывая масштаб компании и сектор (iGaming/Tech), можно ожидать компенсацию на уровне или выше среднего по рынку Амстердама.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Machine Learning Engineer position within the Applied ML & Research team at Superbet. With over 5 years of experience in developing and deploying production-grade machine learning systems, I have a proven track record of building scalable solutions that bridge the gap between research and product impact. My expertise in Python, PyTorch, and XGBoost, combined with a deep understanding of Large Language Models, aligns perfectly with your mission to enhance platform security and user experience.
In my previous roles, I have led the end-to-end ML lifecycle, from data exploration and feature engineering to deploying robust inference pipelines. I am particularly impressed by Superbet's commitment to high engineering standards and responsible ML practices. I am eager to bring my experience with MLflow and AWS to help refine your experimentation hygiene and contribute to the ambitious growth of your global playstack.
Составьте идеальное письмо к вакансии с ИИ-агентом
Откликнитесь в superbet уже сейчас
Присоединяйтесь к команде Superbet и создавайте будущее развлекательных технологий на базе LLM и передового ML!
Описание вакансии
It’s an exciting time to join us! We’re entering new markets, developing new technologies, and moving step by step towards our goal of exciting the world. As our business grows, the number of exciting people initiatives grows with it, and we’re looking for a new colleague to partner with our team to bring these to life.
As a Senior Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.
You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.
What you’ll you be doing:
- Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
- Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
- Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
- Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
- Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
- Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices
We're looking for someone with:
- Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
- 4+ years of industry experience building and deploying ML systems
- Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
- Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
- Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
- Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively
Bonus points for:
- Familiarity with ML tooling such as MLflow, ZenML, or Metaflow
- Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito)
- Exposure to streaming data platforms like Kafka
- Contributions to open-source ML projects
About us
We are a global technology company dedicated to building the future of entertainment and fan-centric experiences.
With commercial markets in Brazil, Belgium, Poland, Romania, and Serbia, our company has evolved from a leading sports betting and gaming operator into a diversified product and tech organization, gathering more than 5,000 dedicated people across our teams.
Shaping the future of play
At Super, we are creating a unique entertainment ecosystem engaging millions of customers worldwide. Our product and technology teams in Amsterdam (the Netherlands), Madrid (Spain), Zagreb (Croatia), London (UK), and Bucharest (Romania) are building the playstack that will champion the future of play.
Our ambitious growth strategy focuses on expanding across Europe and Latin America while delivering immersive customer experiences and creating lasting value for our customers, partners, and communities.
Global recognition and standards
The company’s long-term strategy is supported by world-class investors. In 2019, Blackstone, the world’s largest alternative asset manager, made a strategic minority investment of €175 million. In 2025, we strengthened our financial position through a €1.3 billion refinancing agreement, reinforcing our partnership with Blackstone and enabling accelerated global expansion.
Super is committed to the highest standards of compliance, safety, and responsibility. As such, we are active members of the International Betting Integrity Association (IBIA) and the European Gaming & Betting Association (EGBA).
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Навыки
- AWS
- Python
- PyTorch
- Machine Learning
- Large Language Models
- SQL
- Amazon EKS
- XGBoost
- MLflow
- Apache Kafka
- Amazon EC2
- AWS CloudFormation
- Metaflow
- ZenML
Возможные вопросы на собеседовании
Проверка глубины понимания современных технологий, упомянутых в вакансии.
Расскажите о вашем опыте внедрения LLM в продакшн: с какими основными проблемами задержки (latency) или галлюцинаций вы сталкивались и как их решали?
Вакансия подразумевает работу с полным циклом ML.
Как вы организуете процесс мониторинга моделей после деплоя, чтобы вовремя заметить деградацию качества или дрифт данных?
Упоминание Kafka в бонусах указывает на работу с потоковыми данными.
В чем заключаются основные сложности при обучении моделей на потоковых данных (streaming) по сравнению с батч-обработкой?
Оценка инженерной культуры кандидата.
Опишите ваш подход к обеспечению воспроизводимости экспериментов и тестированию ML-кода. Какие инструменты вы предпочитаете использовать?
Проверка навыков системного дизайна.
Как бы вы спроектировали систему ранжирования для сотен тысяч активных пользователей в реальном времени, учитывая ограничения по памяти и скорости ответа?
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