{"id":2263214,"url":"https://alion.io/job/adesso-senior-machine-learning-engineer-data-scientist","title":"Senior Machine Learning Engineer / Data Scientist","company":{"id":51690,"name":"Adesso","domain":"adesso.de","url":"https://alion.io/company/adesso","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":{"grade":"B","score":80,"open_postings":23,"ghost_share":0,"stale_share":0.783,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-10T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Cologne, Germany"],"countries":["DE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":77000,"max_usd":161000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":13},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Kubeflow","optional":false},{"name":"MLFlow","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-10-01T02:00:00Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-11T22:33:52Z","board_verified":true,"closed_at":null,"days_open":10,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":10},"description":"DEINE ROLLE\nKI-Services entwickeln: Du konzipierst, entwickelst und implementierst neue Machine-Learning-Modelle, die unsere Software intelligent erweitern - etwa für die automatisierte Bewertung medizinischer Daten, Textklassifikation oder Entscheidungsunterstützung in der Rechnungsprüfung.\nModellintegration und MLOps: Du integrierst ML-Modelle nahtlos in unsere Produktarchitektur, automatisierst Trainings- und Deployment-Pipelines und stellst die Nachvollziehbarkeit sowie Wartbarkeit produktiver Modelle sicher.\nQualität und Performance: Du verantwortest die kontinuierliche Überwachung und Verbesserung der Modellqualität, führst Retrainings durch und etablierst Kennzahlen zur Modellbewertung und -optimierung.\nDatenanalyse und Feature Engineering: Du analysierst medizinische und abrechnungsbezogene Daten, leitest relevante Features ab und stellst Datenqualität, -konsistenz und -sicherheit sicher.\nInterdisziplinäre Zusammenarbeit: Du arbeitest eng mit Fachspezialisten, Produktmanagement und Softwareentwicklung zusammen, um KI-basierte Funktionen in unsere Prüfsoftware einzubetten und praxisrelevante Mehrwerte für Krankenkassen und Leistungserbringer zu schaffen.\nDEIN PROFIL\nStudium/Ausbildung: Erfolgreich abgeschlossenes Studium in Informatik, Data Science, Medizininformatik oder einem vergleichbaren Studiengang mit technischem Fokus.\nErfahrung: Mehrjährige Berufserfahrung in der Entwicklung, Implementierung und Betreuung produktiver Machine-Learning-Modelle - idealerweise in einem regulierten oder datengetriebenen Umfeld wie dem Gesundheitswesen, der Versicherung oder dem öffentlichen Sektor.\n Fachskills (ML & Data Science): Fundierte Kenntnisse in Python und den gängigen ML-Frameworks (scikit-learn, TensorFlow, PyTorch) sowie Erfahrung mit Modellbewertung und Feature Engineering.\n Fachskills (MLOps & Architektur): Erfahrung mit MLOps-Tools und -Prozessen (z. 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