{"id":3102908,"url":"https://alion.io/job/visian-ingenieur-mlops-ia","title":"Ingénieur MLOps / IA","company":{"id":3908419,"name":"Visian","domain":"visian.tech","url":"https://alion.io/company/visian","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Welcome to the Jungle","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"freelance","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["France"],"countries":["FR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":48000,"max_usd":105000,"period":"year","method":"role_country_seniority_unknown","sample_n":121},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"MLFlow","optional":false},{"name":"ONNX","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorRT","optional":false}],"status":"live","first_seen_at":"2026-10-22T13:00:35Z","employer_posted_date":null,"last_verified_at":"2026-10-22T13:00:35Z","board_verified":false,"closed_at":null,"days_open":11,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":11},"description":"Contexte de la mission\nLe déploiement des modèles d'IA constitue un nouveau chantier. Les temps d'inférence deviennent de plus en plus importants et nécessitent un diagnostic approfondi pour identifier et prioriser les optimisations.\nLe profiling actuel doit être amélioré afin de mieux comprendre les limites des modèles et de l'infrastructure, de challenger les pistes envisagées et de concentrer les efforts sur les actions les plus pertinentes.\nObjectifs et activités\nDiagnostiquer les performances des modèles et réduire les temps d'inférence sur GPU.\nRéaliser le profiling du code de deep learning, de l'infrastructure et du code compilé.\nAnalyser les traces mémoire et comprendre les comportements d'exécution sur CPU, GPU et dans des environnements multi-GPU.\nUtiliser PyTorch Profiler pour identifier les goulots d'étranglement.\nÉvaluer, challenger et prioriser les pistes d'optimisation.\nAméliorer l'export des modèles et leur optimisation pour l'inférence, notamment avec ONNX et TensorRT.\nContribuer à la gestion et à l'utilisation efficace des ressources GPU.\nAccompagner les clients internes sur la chaîne allant de l'entraînement au déploiement des modèles.\nAssurer la traçabilité des expérimentations avec MLflow.\nVulgariser les diagnostics et les recommandations auprès des équipes concernées.\nProfil recherché\nCompétences recherchées\nExpérience en ingénierie IA / MLOps et en développement logiciel.\nMaîtrise de PyTorch et du profiling de modèles de deep learning.\nBonne compréhension de l'exécution et de la gestion mémoire sur GPU.\nExpérience des environnements CPU, GPU et multi-GPU.\nConnaissance d'ONNX, de TensorRT et de MLflow.\nCapacité à poser un diagnostic, à hiérarchiser les actions et à expliquer les 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Docs: https://alion.io/developers"}}