{"id":3737099,"url":"https://alion.io/job/twentyfour-industries-ai-engineer-computer-vision-mlops","title":"AI Engineer Computer Vision & MLOps","company":{"id":3894744,"name":"Twentyfour Industries","domain":"twentyfour-industries.com","url":"https://alion.io/company/twentyfour-industries","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Personio","truth_index":{"grade":"B","score":70,"open_postings":12,"ghost_share":0.583,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":20,"computed_at":"2026-11-09T06:03:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Munich, Germany"],"countries":["DE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":true,"has_equity":true,"technologies":[{"name":"CI/CD","optional":false},{"name":"CNN","optional":false},{"name":"Computer Vision","optional":false},{"name":"Machine Learning","optional":false},{"name":"ONNX","optional":false},{"name":"Perception","optional":false},{"name":"PyTorch","optional":false},{"name":"Synthetic Data","optional":false},{"name":"TensorRT","optional":false},{"name":"Isaac Sim","optional":true}],"status":"live","first_seen_at":"2026-07-30T09:37:14Z","employer_posted_date":"2026-07-30","last_verified_at":"2026-11-09T03:27:44Z","board_verified":true,"closed_at":null,"days_open":102,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":101},"description":"What we’re looking for\nWe're looking for a highly driven Computer Vision / ML Engineer to own the data, training, evaluation, and MLOps lifecycle for our camera-based perception models. In this role, you'll turn real and synthetic drone data into reproducible, validated model releases, building and operating the pipelines that connect collection, annotation, training, evaluation, and release. This is an ownership role where you'll work closely with robotics perception engineers, directly shaping how reliably our systems see and understand the world.The day-to-day\nRequirements definition: define clear objectives, interfaces, datasets, and release standards for deep learning tasks such as detection, segmentation, and depth\nData strategy: drive real-world and synthetic data collection campaigns covering edge cases, rare conditions, and class imbalance\nDataset integrity: build trusted, versioned, auditable datasets, maintaining lineage and preventing leakage across every model release\nModel performance: develop, train, and benchmark detection, segmentation, and depth-estimation models for aerial imagery\nEvaluation rigor: set a high bar for evaluation and failure analysis across range, altitude, illumination, and weather conditions\nMLOps ownership: build and operate the end-to-end pipeline for versioning, reproducible training, experiment tracking, and CI/CD\nDeliver production-ready model artifacts. Export and optimize models for ONNX and TensorRT, validate accuracy and runtime performance.\nYou should apply if you\nComputer vision depth: you have a deep understanding of CNN- and transformer-based architectures, training dynamics, and evaluation, with hands-on PyTorch experience\nDataset discipline: you're experienced building representative dataset splits, validating annotations, and conducting detailed failure analysis\nMLOps experience: you have end-to-end production MLOps ownership, including experiment tracking, versioning, and CI/CD\nSoftware engineering: you write clean, tested, maintainable code and make sound performance and algorithmic trade-offs\nTrack record: you bring 3+ years building and shipping computer-vision or ML systems with ownership across data, training, and evaluation\nEducation: you hold a degree in computer science, machine learning, or a related field - or equivalent hands-on experience that speaks louder than the diplom\nNice to haves\nAerial vision: experience with drone imagery, small-object detection, or low-light and low-resolution data\nSimulation expertise: hands-on experience with NVIDIA Isaac Sim, Omniverse, or other synthetic-data workflows\nInference optimization: experience exporting and optimizing models with ONNX and TensorRT on NVIDIA Jetson hardware\nWhat we offer\nReal impact & ownership:Shape high-tech defensesystems and take responsibility from day one.\nMission-driven environment: Work on technologies that matter for European security and sovereignty.\nCompetitive package:Competitive salary, EGYM Wellpass, corporate benefits, and equity options aligned with role and level.\nDeep tech environment:Get hands-on experience with cutting-edge drone technology and real operational use cases.\nGrow fast: Steep learning curve for juniors, strategic influence and leadership opportunities for seniors.\nStartup mindset meets defenceinnovation:flat hierarchies, fast decisions, and space for your ideas.\nFlexibility:Flexible 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