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Senior Machine Learning Engineer - Applied ML & Research
Оценка ИИОтличная позиция в крупной международной компании с серьезными инвестициями (Blackstone). Работа над передовыми технологиями (LLM, Applied Research) и возможность влиять на продукт с миллионами пользователей делают вакансию крайне привлекательной.
Сложность вакансии
Оценка ИИРоль требует глубоких знаний в области ML-фундаментала и практического опыта работы с LLM. Высокая планка ожидается в вопросах качества кода и построения надежных пайплайнов (MLOps), что характерно для уровня Senior.
Анализ зарплаты
Оценка ИИПредлагаемая позиция Senior уровня в Испании соответствует рыночным ожиданиям для крупных технологических компаний. Оценка базируется на данных по Мадриду и Барселоне для специалистов с опытом 4+ года и навыками в области LLM.
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 4 years of experience in building and deploying scalable ML systems and a deep focus on Large Language Models (LLMs), I am excited about the opportunity to impact platform security and user experience for your global gaming audience. My background in developing robust training and inference pipelines, combined with a commitment to engineering excellence, aligns perfectly with Superbet's mission to build a world-class playstack.
In my previous roles, I have successfully led the end-to-end ML lifecycle, from data exploration to production monitoring, using tools like PyTorch and XGBoost. I am particularly drawn to this role because of Superbet's ambitious growth and the chance to work on diverse use cases like ranking, retrieval, and LLM integration. I am confident that my technical expertise in Python and SQL, along with my experience in cross-functional collaboration, will allow me to contribute immediately to your team's standards and the overall ML roadmap.
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Откликнитесь в superbet уже сейчас
Присоединяйтесь к команде Superbet и создавайте будущее развлекательных технологий на основе LLM и передового машинного обучения!
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
- Kafka
- XGBoost
- MLflow
- CloudFormation
- Amazon EC2
- Data Science
- Metaflow
- ZenML
Возможные вопросы на собеседовании
Проверка глубины понимания современных технологий, указанных в требованиях.
Расскажите о вашем опыте внедрения LLM в продакшн: с какими основными проблемами (галлюцинации, задержки, стоимость) вы столкнулись и как их решили?
Оценка навыков проектирования систем (System Design) для высоконагруженных платформ.
Как бы вы спроектировали систему ранжирования в реальном времени для сотен тысяч пользователей, учитывая необходимость низкой задержки?
Проверка инженерной культуры и понимания жизненного цикла ML.
Какие практики тестирования и мониторинга ML-моделей вы считаете обязательными для обеспечения воспроизводимости и надежности в продакшене?
Оценка способности работать с неопределенностью, что важно для R&D команды.
Опишите случай, когда вы превратили абстрактную бизнес-задачу в конкретный ML-проект. Как вы определяли метрики успеха?
Проверка навыков работы с данными и SQL.
Как вы подходите к проектированию признаков (feature engineering) для моделей классификации, если данные поступают из стриминговых платформ вроде Kafka?
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