CDI - AI Data Scientist F/H

A propos de vos missions VOTRE RÔLE En tant qu’Ingénieur en Intelligence Artificielle, vous serez responsable de la conception, du déploiement et de l’amélioration continue d’équipements physiques destinés à automatiser ou remplacer des tâches manuelles dans les environnements de fabrication de semi‑conçucteurs. At STMicroelectronics, we believe in the power of technology to drive innovation and make a positive impact on people, businesses, and society. As a global semiconductor company, our advanced technologies and chips form the hidden foundation of the world we live in today. When you join ST, you will be part of a global business with more than 115 nationalities, present in 40 countries, and comprising over 50,000 diverse and dedicated creators and makers of technology around the world. Developing technologies takes more than talent: it takes amazing people who understand collaboration and respect. People with passion and the desire to disrupt the status quo, drive innovation, and unlock their own potential. Embark on a journey with us, where you can innovate for a future that we want to make smarter and greener, in a responsible and sustainable way. Our technology starts with you. English version About Your Missions YOUR ROLE The AI Engineer leads the design, deployment, and continuous improvement of physical assets to augment or replace manual tasks in semiconductor manufacturing environments. Key Responsibilities AI Model Identification & Development Analyze technician/operator workflows to identify repetitive, high-precision, or hazardous tasks suitable for AI/physical automation. Develop, train, and validate embodied AI models leveraging Vision-Language Models (VLM) and Vision-Language-Action (VLA) frameworks to enable integrated perception, natural language understanding, and task execution capabilities. Utilize NVIDIA Omniverse or similar simulation platforms for high-fidelity 3D simulation and digital twin environments to train, test, and optimize physical assets AI models in realistic virtual manufacturing settings. Integrate multimodal data (image, sensor, process logs, SPC data) into AI models for robust decision‑making and adaptive control. Continuously improve models using feedback from simulation and real‑world performance. Physical manufacturing asset System Integration Collaborate with robotics vendors to adapt physical assets or semiconductor environments (cleanroom compliance, ESD safety, precision control). Integrate AI models with physical asset control systems and factory MES/SCADA systems. Configure robots/related physical asset for complex task execution such as wafer cassette transfer, equipment start‑up/shutdown, parameter verification, inline inspection, and reporting. Simulation and Virtual Training Environment Development Design and maintain simulation scenarios within Omniverse/similar platform to replicate manufacturing processes and environments for embodied AI training. Employ VLM and VLA techniques to simulate realistic robot‑environment interactions, enabling the AI to learn visual perception coupled with language understanding and action planning. Validate AI behavior in virtual environments before physical deployment to reduce risk and improve efficiency. Testing, Validation, and Qualification Define test plans to validate robot/physical asset accuracy, repeatability, and safety before deployment. Establish qualification metrics: task success rate, downtime reduction, human replacement efficiency. Work with EHS to ensure compliance with safety and cleanroom standards. Deployment and Continuous Improvement Lead pilot projects for physical manufacturing asset-assisted lines and scale up successful deployments. Analyze performance data, identify model drift or mechanical degradation, and retrain models as needed. Conduct root‑cause analysis for failed or abnormal tasks. Provide ongoing model tuning and system maintenance. Cross‑Functional Collaboration Work closely with process engineers, maintenance teams, IT, and data scientists. Serve as the liaison between physical manufacturing assets providers and internal automation engineering teams. Train human technicians to supervise and interact with physical manufacturing assets systems safely. About You YOUR SKILLS & EXPERIENCES Technical Skills Strong understanding of semiconductor manufacturing processes (Front‑End and/or Back‑End). Proficiency in AI/ML model development (Python, TensorFlow/PyTorch, OpenCV). Experience with embodied AI frameworks such as Vision‑Language Models (VLM) and Vision‑Language‑Action (VLA) for integrated perception, language understanding, and action modeling. Hands‑on experience with NVIDIA Omniverse or similar simulation platforms for digital twin and virtual training environments. Experience with robotic/humanoid platforms (e.g., Boston Dynamics, UBTech, Hanson Robotics, or custom cobots). Knowledge of robot control systems (ROS, PLC interfacing, motion planning). Familiar with machine vision systems, defect detection, and sensor fusion. Integration of AI models with edge devices and factory systems (OPC‑UA, MQTT, MES APIs). Experience in cloud technologies is added advantage. Soft Skills Analytical and innovative mindset. Strong cross‑disciplinary collaboration. Clear communication between data science, robotics, and operations teams. Strong documentation and safety awareness. Education & Experience Bachelor’s or Master’s degree in Robotics, AI/ML, Mechatronics, Electrical Engineering, or Computer Science. 3–8 years’ experience in semiconductor manufacturing, robotics automation, or AI model deployment. Experience deploying AI/vision models in industrial environments (manufacturing, automotive, electronics) is a plus. Prior experience with embodied AI training using VLM, VLA, and Omniverse highly desirable. This role may require candidate to travel between different manufacturing sites of the company. Experience with cleanroom operation or ISO 14644 standards preferred. A propos de vous Vos Competences Et Experiences Compétences techniques Bonne connaissance des processus de fabrication de semi‑conducteurs (Front‑End et/ou Back‑End). Maîtrise du développement de modèles IA/ML (Python, TensorFlow/PyTorch, OpenCV). Expérience avec les frameworks d’IA incarnée tels que Vision‑Language Models (VLM) et Vision‑Language‑Action (VLA) pour la perception intégrée, la compréhension du langage et la modélisation d’actions. Pratique des plateformes de simulation comme NVIDIA Omniverse pour la création de jumeaux numériques et d’environnements de formation virtuelle. Expérience avec des plateformes robotiques/humanoïdes (ex. Boston Dynamics, UBTech, Hanson Robotics, ou cobots personnalisés). Connaissance des systèmes de contrôle robotique (ROS, interface PLC, planification de mouvements). Familiarité avec les systèmes de vision industrielle, la détection de défauts et la fusion de capteurs. Intégration des modèles IA avec des dispositifs edge et les systèmes d’usine (OPC‑UA, MQTT, API MES). Une expérience en technologies cloud est un plus. Compétences comportementales Esprit analytique et innovant. Forte capacité de collaboration interdisciplinaire. Communication claire entre équipes data science, robotique et opérations. Rigueur dans la documentation et conscience des enjeux de sécurité. Formation & expérience Diplôme de niveau Bac+3 à Bac+5 en Robotique, IA/ML, Mécatronique, Génie électrique ou Informatique. 3 à 8 ans d’expérience dans la fabrication de semi‑conducteurs, l’automatisation robotique ou le déploiement de modèles IA. Une expérience dans le déploiement de modèles IA/vision en environnement industriel (manufacturier, automobile, électronique) est un plus. Une expérience préalable en entraînement d’IA incarnée avec VLM, VLA, et Omniverse est fortement souhaitée. Ce poste peut nécessiter des déplacements entre différents sites de production du groupe. Une expérience en environnement salle blanche ou connaissance des normes ISO 14644 est un atout. ST is proud to be one of the 17 companies certified as a 2025 Global Top Employer and the first and only semiconductor company to achieve this distinction. ST was recognized in this ranking thanks to its continuous improvement approach and stands out particularly in the areas of ethics & integrity, purpose & values, organization & change, business strategy, and performance. At ST, we endeavor to foster a diverse and inclusive workplace, and we do not tolerate discrimination. We aim to recruit and retain a diverse workforce that reflects the societies around us. We strive for equity in career development, career opportunities, and equal remuneration. We encourage candidates who may not meet every single requirement to apply, as we appreciate diverse perspectives and provide opportunities for growth and learning. Diversity, equity, and inclusion (DEI) is woven into our company culture. To discover more, visit st.com/careers. #J-18808-Ljbffr