{"id":105269,"url":"https://alion.io/job/zeiss-machine-learning-engineer-mfx","title":"Machine Learning Engineer (m/f/x)","company":{"id":5290,"name":"Zeiss","domain":"zeiss.com","url":"https://alion.io/company/zeiss","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":77,"open_postings":247,"ghost_share":0,"stale_share":0.935,"repost_share":0,"time_to_fill_p50_days":26,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Oberkochen, Germany"],"countries":["DE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":60000,"max_usd":140000,"period":"year","method":"role_country_seniority_unknown","sample_n":61},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Ansible","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Bicep","optional":false},{"name":"C#","optional":false},{"name":"C++","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"DVC","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-07-21T00:00:00Z","employer_posted_date":"2026-07-21","last_verified_at":"2026-10-17T05:49:45Z","board_verified":true,"closed_at":null,"days_open":88,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":88},"description":"At ZEISS Corporate Research & Technology, we work at the frontier of science and technology. Our mission is to innovate and develop intelligent solutions contributing directly to future ZEISS products.We’relooking for a Machine Learning Engineer (f/m/x) who enjoys working across disciplines and is eager to develop intelligent systems that make a real difference for our consumers.\nYour role\nArchitect the ML Platform: Design, implement, and maintain a robust MLOps infrastructure that enables researchers to move seamlessly from local experimentation to global production.\n\nProductionalize Research: Act as the \"Engineering Bridge\" by transforming experimental research code into modular, high-performance, and maintainable Python/C++ software packages.\n\nAutomation & CI/CD: Build and manage sophisticated automated pipelines for testing, building, and deploying ML models across diverse ZEISS product environments (Cloud, Edge, and On-premise).\n\nInfrastructure as Code (IaC): Own the provisioning and scaling of our research computing environments using Terraform and Ansible, ensuring high availability and resource efficiency.\n\nEstablish Engineering Standards: Define and promote best practices for the entire department, including version control (Git), containerization (Docker), code quality (linting/testing), and documentation.\n\nObservability & Lifecycle Management: Implement advanced monitoring and logging solutions (e.g., MLflow, ELK stack) to track model performance, data drift, and system health in real-world applications.\n\nCollaborative Consulting: Serve as the internal expert and consultant for scientists, helping them optimize their workflows and navigate the complexities of modern cloud and hardware environments.\n\nYour profile\nEngineering Foundation: You hold an excellent university degree in Computer Science, Software Engineering, or a related technical field. 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