{"id":554465,"title":"Senior Machine Learning Engineer","company":"Globaldev Group","city":null,"region":null,"location":"","work_model":"remote","employment_type":"unknown","employment":["full_time"],"roles":["data_science"],"visa":"not_mentioned","relocation":"not_mentioned","posted_at":"2026-03-13T00:00:00+00:00","tools":["Python","pandas","scikit-learn","PyTorch","MLOps","CI/CD"],"seniority":"senior","years_experience_min":5,"german_requirement":"not_mentioned","german_level":"unspecified","english_requirement":"required","english_level":"unspecified","team_language":"unknown","confidence":0.4,"method":"rules","language_badge":"English ad, no German stated","badge_key":"english_ad","language_evidence":null,"requirements_snippet":"5+ years of experience in machine learning / applied ML roles with production ownership Proven track record of deploying and maintaining ML systems in real-world environments Strong Python skills (e.g., pandas, scikit-learn, …","url":"https://apply.workable.com/j/33DC3FF471","source":"workable","agency":null,"description_text":"We are looking for a Senior Machine Learning Engineer to design, own, and scale predictive systems that power VIS.X - programmatic advertising platform.\nYou will take end-to-end responsibility for high-impact ML initiatives (e.g., pricing optimization, bid prediction, performance forecasting, delivery optimization) and translate complex business problems into robust, production-grade machine learning systems.\nThis is a senior individual contributor role with leadership potential. You will help shape our ML architecture, standards, and long-term AI strategy, with the opportunity to grow into a team lead role as we expand our data science capabilities.\nRequirements:\n• 5+ years of experience in machine learning / applied ML roles with production ownership\n• Proven track record of deploying and maintaining ML systems in real-world environments\n• Strong Python skills (e.g., pandas, scikit-learn, PyTorch/TensorFlow)\n• Solid knowledge of statistics, experimentation design, and model evaluation\n• Experience working with large-scale datasets and performance-critical systems\n• Understanding of MLOps principles (model lifecycle, monitoring, CI/CD integration, retraining pipelines)\n• Strong problem ownership mindset - ability to independently structure ambiguous challenges\n• Ability to translate business trade-offs into modeling decisions\n• Experience in AdTech, marketplaces, or auction-based systems is a plus\n• Experience working in high-scale, real-time systems is a plus\nResponsibilities:\n• Take ownership of machine learning problems from concept to production\n• Design, build, and deploy predictive models (e.g. pricing, bidding, optimization, forecasting)\n• Develop scalable feature engineering and data pipelines for large-scale datasets\n• Define experimentation frameworks (A/B testing, offline validation, model comparison)\n• Ensure production-grade MLOps: monitoring, retraining, drift detection, reliability\n• Collaborate closely with DevOps, Product, Engineering teams to align ML with business impact\n• Quantify model impact on revenue, margin, and performance KPIs\n• Contribute to building our long-term ML architecture and best practices\nWhat we offer:\n• Comfortable environment, challenging tasks and a long-term interesting project;\n• Covered 20 days of vacation;\n• Working with top notch equipment;\n• Bookkeeping by a professional accountant;\n• Help and support from our caring HR-team;","responsibilities_text":"• Take ownership of machine learning problems from concept to production\n• Design, build, and deploy predictive models (e.g. pricing, bidding, optimization, forecasting)\n• Develop scalable feature engineering and data pipelines for large-scale datasets\n• Define experimentation frameworks (A/B testing, offline validation, model comparison)\n• Ensure production-grade MLOps: monitoring, retraining, drift detection, reliability\n• Collaborate closely with DevOps, Product, Engineering teams to align ML with business impact\n• Quantify model impact on revenue, margin, and performance KPIs\n• Contribute to building our long-term ML architecture and best practices","requirements_text":"• 5+ years of experience in machine learning / applied ML roles with production ownership\n• Proven track record of deploying and maintaining ML systems in real-world environments\n• Strong Python skills (e.g., pandas, scikit-learn, PyTorch/TensorFlow)\n• Solid knowledge of statistics, experimentation design, and model evaluation\n• Experience working with large-scale datasets and performance-critical systems\n• Understanding of MLOps principles (model lifecycle, monitoring, CI/CD integration, retraining pipelines)\n• Strong problem ownership mindset - ability to independently structure ambiguous challenges\n• Ability to translate business trade-offs into modeling decisions\n• Experience in AdTech, marketplaces, or auction-based systems is a plus\n• Experience working in high-scale, real-time systems is a plus","status":"open","duplicate_of":null,"first_seen":"2026-11-14T04:17:02.787853+00:00","responsibilities_summary":null,"requirements_summary":null,"all_tools":["Python","pandas","scikit-learn","PyTorch","MLOps","CI/CD"],"posting_language":"en","evidence":[],"years_experience_max":null,"mobility_evidence":[],"model_version":"rules-11","english_badge":"English required","company_id":211166}