{"id":2658545,"url":"https://alion.io/job/super-staff-machine-learning-engineer-applied-ml-research","title":"Staff Machine Learning Engineer - Applied ML & Research","company":{"id":2032361,"name":"Super","domain":"super.xyz","url":"https://alion.io/company/super-xyz","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"C","score":67,"open_postings":35,"ghost_share":0.543,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-16T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Netherlands"],"countries":["NL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":96000,"max_usd":218000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1148},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon SageMaker","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"XGBoost","optional":false},{"name":"Amazon EC2","optional":true},{"name":"Amazon EKS","optional":true},{"name":"Apache Kafka","optional":true},{"name":"AWS","optional":true},{"name":"CloudFormation","optional":true},{"name":"Kubernetes","optional":true},{"name":"Metaflow","optional":true},{"name":"MLFlow","optional":true}],"status":"live","first_seen_at":"2024-11-18T21:47:28Z","employer_posted_date":"2026-09-30","last_verified_at":"2026-10-16T02:52:42Z","board_verified":true,"closed_at":null,"days_open":696,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":696},"description":"We are on a mission to pioneer the world’s next era of play. As we grow across Europe and Latin America, we’re building The Playstack - the technology powering the next generation of sports, gaming, and fan experiences. Join us, and help make it the most widely used platform in the world! From operations, to marketing, to product, we are looking for talented people who will shape how millions of customers play, watch, and connect every day.\nAs a Staff Machine Learning Engineer in the Applied ML & Research team, you'll drive the development of 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. This role blends hands-on technical work with strategic thinking - you'll lead by example, contribute high-quality code, and help shape the ML roadmap through cross-functional collaboration.\nWhat the role involves\nIdentify high-impact ML opportunities and influence stakeholders to prioritise and support these initiatives\nDesign and develop scalable machine learning models - including classifiers, regressors, and rule-based systems - to solve real-world problems\nOwn the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment\nTranslate complex technical concepts into clear insights for both technical and non-technical stakeholders\nSet and guide technical direction across ML projects, ensuring alignment with technical best practices and business goals\nMentor junior engineers and foster a culture of knowledge sharing and continuous improvement\nWhat we are looking for\nMaster's degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field\n7+ years of industry experience building and deploying ML models at scale\nProven ability to lead cross-functional technical initiatives and influence engineering strategy\nProficiency in Python (with libraries such as PyTorch, XGBoost, and Scikit-learn) and SQL\nStrong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar\nDeep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies\nA track record of shipping production-level ML products and maintaining high code quality\nExcellent problem-solving skills and the ability to scope and disambiguate complex ML projects into clear, achievable milestones\nNice to have\nFamiliarity with ML tooling such as MLflow, ZenML, or Metaflow\nHands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito)\nExposure to streaming data platforms such as Kafka\nContributions to open-source ML projects or publications in ML conferences\nWhat we offer\nMedical / Health Insurance\nOpen Annual Leave\nEmployee Assistance Programme\nTraining & Learning Development\nAdditional benefits vary by country and will be shared during the hiring process.\nAbout Super\nWe are a global technology group, dedicated to building the future of entertainment and fan-centric experiences. With commercial markets in Brazil, Belgium, Poland, Romania, Greece and Serbia, and a network of offices across Spain, Croatia, Malta, Gibraltar, the Netherlands and the UK, we are a truly international organization. Our purpose at Super has evolved from sports and betting into creating the platform that stretches into the wider world of technology-driven entertainment. With a growing and diverse team of more than 5,000 people, we create immersive, responsible, and personalised experiences for millions of customers worldwide.\nShaping the Future of Play\nEverything we do at Super is rooted in doing what is right: for customers, for each other, and for our long-term vision. Our Culture Manifesto is our North Star. It captures our purpose, mission, and the six core beliefs that shape how we think, make decisions, and act every day. Want to explore our culture in more detail? Visit our careers page: super.xyz/careers \nSuper 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).\nAt Super, we operate as a high-performing team. 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