Stagiaire développeur(euse) outils logiciels job opportunity at GE Vernova.

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DateMore Than 30 Days Ago bot
GE Vernova Stagiaire développeur(euse) outils logiciels
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Pattern: full-time
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degreeMaster's (M.A.)
loacation Montpellier, France
loacation Montpellier....France

Job Description Summary Job Description Poste et missions : Au sein de l’équipe Support Level 3 – Grid Automation, vous participerez au développement d’outils logiciels internes visant à analyser, automatiser et fiabiliser le traitement de données techniques et opérationnelles (tickets de support, métriques, configurations, logs). Vos missions incluront : ·         Conception et développement d’applications backend en Python ·         Mise en place de pipelines de traitement de données (batch et/ou asynchrones) ·         Développement de services conteneurisés (Docker) et de workers (Celery) ·         Implémentation de tests unitaires et fonctionnels ·         Participation à la validation et au déploiement des outils Selon le profil et l’appétence du/de la stagiaire, une contribution à des fonctionnalités intégrant des briques Data ou Intelligence Artificielle (analyse de données, automatisation, intégration de modèles existants) pourra être envisagée : ·         Analyse automatique de données (classification, détection d’erreur et d’anomalies, NLP) ·         Intégration de modèles existants (ML / LLM) dans des workflows logiciels ·         Implémenter des pipelines de traitement de données (nettoyage, transformation, validation) Profil et compétences requises : Compétences techniques – Requises ·         Développement logiciel en Python Bonne maîtrise du langage et de ses écosystèmes Capacité à structurer un projet (modules, packages, bonnes pratiques) Écriture de code maintenable, lisible et documenté ·         Architecture logicielle & backend Compréhension des principes de microservices Développement de services backend exposant des APIs REST Gestion des échanges de données (JSON, XML) ·         Traitement et analyse de données Manipulation, nettoyage et validation de données structurées Capacité à concevoir des pipelines de traitement de données Sensibilité à la qualité, la cohérence et la traçabilité des données ·         Bases de données Maîtrise de SQL Conception et interrogation de bases de données relationnelles Compréhension des modèles de données et des relations ·         Asynchronisme & traitement distribué Notions de traitements asynchrones Utilisation ou compréhension de systèmes de files de messages et de workers Sensibilisation aux problématiques de performance et de montée en charge ·         Qualité logicielle Écriture de tests unitaires et fonctionnels Débogage et analyse d’erreurs Respect des cycles de développement logiciel (conception → développement → validation → livraison) ·         Outils & collaboration Utilisation de Git / GitHub (versioning, branches, revues de code) Travail en environnement collaboratif et structuré Compétences techniques – Appréciées ·         Conteneurisation Docker (création et utilisation de conteneurs) Compréhension des environnements reproductibles ·         Traitements distribués Expérience ou notions autour de Celery et Redis Orchestration de tâches longues ou intensives ·         APIs & intégration Conception d’APIs REST robustes Intégration avec des systèmes existants Data & Intelligence Artificielle – Optionnel mais valorisé ·         Connaissances de base en Data Science / Machine Learning ·         Intérêt ou expérience dans un ou plusieurs domaines : NLP (Natural Language Processing) Computer Vision IA Générative / LLMs ·         Utilisation ou compréhension de : Librairies ML existantes APIs de modèles IA ·         Notions de : Préparation et validation des données pour des usages IA Intégration de briques IA dans des applications logicielles Langues ·         Anglais professionnel (lu, écrit, parlé) Savoir être ·         Rigueur, communication écrite, travail en équipe, adaptation Formation : Diplôme préparé : Master 2 Domaine/spécialité de formation : Développement logiciel ENGLISH: Position and Responsibilities: As part of the Level 3 Support – Grid Automation team, you will participate in the development of internal software tools aimed at analyzing, automating, and ensuring the reliability of technical and operational data processing (support tickets, metrics, configurations, logs). Your responsibilities will include: · Design and development of backend applications in Python · Implementation of data processing pipelines (batch and/or asynchronous) Development of containerized services (Docker) and workers (Celery) · Implementation of unit and functional tests · Participation in the validation and deployment of tools Depending on the intern's profile and interest, contributions to features involving Data or Artificial Intelligence components (data analysis, automation, integration of existing models) may be considered: · Automatic data analysis (classification, error and anomaly detection, NLP) · Integration of existing models (ML / LLM) into software workflows · Implementing data processing pipelines (cleaning, transformation, validation) Profile and Required Skills: Technical Skills – Required · Software Development in Python Good command of the language and its ecosystems Ability to structure a project (modules, packages, best practices) Writing maintainable, readable, and well-documented code · Software Architecture & Backend Understanding of microservices principles Development of backend services exposing REST APIs Management of data exchanges (JSON, XML) Data processing and analysis Manipulation, cleaning, and validation of structured data Ability to design data processing pipelines Attention to data quality, consistency, and traceability · Databases Proficiency in SQL Designing and querying relational databases Understanding of data models and relationships Asynchrony & distributed processing Concepts of asynchronous processing Use or understanding of message queue systems and workers Awareness of performance and scalability issues · Software quality Writing unit and functional tests Debugging and error analysis Adherence to software development cycles (design → development → validation → delivery) Tools & Collaboration Use of Git / GitHub (versioning, branches, code reviews) Working in a collaborative and structured environment Technical Skills – Appreciated · Containerization Docker (creating and using containers) Understanding of reproducible environments · Distributed Processing Experience or knowledge of Celery and Redis Orchestration of long or intensive tasks APIs & Integration Design of robust REST APIs Integration with existing systems Data & Artificial Intelligence – Optional but valued · Basic knowledge in Data Science / Machine Learning · Interest or experience in one or more areas: NLP (Natural Language Processing) Computer Vision Generative AI / LLMs Use or understanding of: Existing ML libraries AI model APIs ·         Concepts of: Data preparation and validation for AI purposes Integration of AI components into software applications Languages · Professional English (read, written, spoken) Soft Skills · Precision, written communication, teamwork, adaptability Education: Degree Pursued: Master’s Degree (Level 2) Field/Specialization: Software Development

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