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Senior Machine Learning Engineer - Applied ML & Research
Отличная позиция в крупной международной компании с серьезной финансовой поддержкой (Blackstone). Работа над высоконагруженными системами и использование современных технологий (LLM, AWS, Kafka) делают вакансию крайне привлекательной для профессионального роста.
Сложность вакансии
Роль требует глубоких знаний в области ML-фундаментала и практического опыта работы с LLM. Высокая планка ожидается в вопросах качества кода и умения декомпозировать неопределенные задачи в условиях быстрорастущего бизнеса.
Анализ зарплаты
Зарплата в вакансии не указана, но для уровня Senior ML Engineer в Румынии рыночный диапазон составляет от 5500 до 8500 евро чистыми в месяц. Учитывая глобальный статус Superbet и инвестиции, можно ожидать предложение по верхней границе рынка плюс бонусы.
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 four years of experience in building and deploying scalable ML systems and a deep fascination with Large Language Models, I am eager to contribute to a platform that serves hundreds of thousands of users daily. My background in developing robust training and inference pipelines, combined with a commitment to engineering excellence, aligns perfectly with Superbet's mission to deliver immersive and secure customer experiences.
In my previous roles, I have successfully bridged the gap between complex research and production-ready code, utilizing tools like PyTorch and XGBoost to solve real-world problems. I am particularly impressed by Superbet's global expansion and the strategic focus on data-driven decision-making. I am confident that my technical skills in Python, SQL, and emerging ML technologies, along with my experience in cross-functional collaboration, will allow me to make a significant impact on your ML roadmap and help shape the future of play.
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Откликнитесь в superbet уже сейчас
Присоединяйтесь к команде Superbet и создавайте будущее развлекательных технологий на основе LLM и продвинутого 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
- Large Language Models
- SQL
- Amazon EKS
- XGBoost
- MLflow
- Apache Kafka
- Amazon EC2
- AWS CloudFormation
- Metaflow
- ZenML
- Amazon Cognito
Возможные вопросы на собеседовании
Проверка глубины понимания современных архитектур, упомянутых в вакансии.
Расскажите о вашем опыте внедрения LLM в продакшн: с какими основными проблемами (галлюцинации, задержки, стоимость) вы столкнулись и как их решили?
Вакансия подразумевает работу над безопасностью и пользовательским опытом.
Как бы вы спроектировали систему ранжирования для игрового контента, учитывая необходимость обновления данных в реальном времени через Kafka?
Оценка навыков MLOps и воспроизводимости.
Какие инструменты (например, MLflow или ZenML) вы считаете наиболее эффективными для обеспечения воспроизводимости экспериментов в распределенной команде?
Проверка инженерной культуры.
Опишите ваш подход к тестированию ML-моделей перед деплоем. Какие метрики, помимо точности, вы считаете критическими для мониторинга в продакшене?
Оценка способности работать с бизнесом.
Приведите пример, когда вам пришлось объяснять технические ограничения выбранной модели нетехническим стейкхолдерам. Как это повлияло на итоговый продукт?
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