ph3Machine Learning Engineer /h3 pAs a Machine Learning Engineer in our Applied ML Research team, you will 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. /p h3Responsibilities /h3 ul liPartner with product and engineering to identify and execute machine learning use cases that deliver measurable impact. /li liDesign, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule‑based components). /li liContribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring. /li liImplement reliable training/inference pipelines and help improve reproducibility, testing, and observability. /li liCommunicate model behavior, trade‑offs, and results clearly to both technical and non‑technical stakeholders. /li liContribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices.



/li /ul h3Qualifications /h3 ul liBachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus). /li li2+ years of industry experience building and deploying ML systems. /li liSolid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL. /li liDeep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies. /li liDemonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices. /li liStrong problem‑solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively. /li /ul h3Bonus Points /h3 ul liFamiliarity with ML tooling such as MLflow, ZenML, or Metaflow. /li liHands‑on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito). /li liExposure to streaming data platforms like Kafka. /li liContributions to open‑source ML projects. /li /ul /p #J-18808-Ljbffr

📌 Machine Learning Engineer - Applied ML & Research (Madrid)
🏢 Superbet
📍 Madrid