At Schneider Electric, we are committed to solving real-world problems to create a sustainable, digitized, new electric future. Artificial Intelligence has the potential to transform industries and help unlock efficiency and sustainability. Within our Global AI Hub we combine our long-standing manufacturing and domain expertise with cutting-edge innovation in AI, machine learning, and deep learning to empower smarter decision-making, agility, and decarbonization. Our Strategy & Innovation team drives the AI strategy and innovation efforts for the AI Hub, Schneider Digital, and Schneider Electric at large. We are building the next generation of intelligent systems that combine large-scale multimodal models, graph/topology understanding, simulation, and domain logic to enable system-level reasoning across energy, buildings, industry, and data centers. Your role : We’re looking for a curious, fast-moving applied research scientist who loves turning cutting-edge papers into prototypes and pushing them further. You combine strong transformer fundamentals with rigorous experimentation, solid engineering habits, and an end-to-end maker mindset - from preparing the data to building the model to crafting demos that make the value visible. You thrive in a collaborative environment, engage actively with the research community, and enjoy working with product and business teams to translate ideas into real impact. Your responsibilities : Develop advanced representations for core modalities — time series, tabular, text, and graph/topology, visual/3D data Rapidly translate state-of-the-art research into prototypes, adapting multimodal and transformer-based architectures to Schneider-specific datasets Build robust, reproducible ML pipelines, covering data preparation, experiment tracking, baselines, ablations Lead the creation and preparation of multimodal datasets, transforming raw data (such as time-series signals, structured tables, documents, diagrams, and system relationships) into clean, usable training datasets Collaborate with domain experts and product teams to align modeling choices with physical constraints and convert prototypes into clear, impactful demonstrations Your profile : Required Qualifications PhD in Machine Learning, AI, Computer Vision, NLP, Robotics, or related field with strong foundations in transformers and modern representation learning. We are also open to exceptional candidates from top Master’s programs or leading engineering schools with demonstrated research or applied excellence Demonstrated experience in multimodal ML, with strong skills in at least two core modalities: Time-series modeling (e.g., forecasting, anomaly detection, foundation models) Tabular/structured data modeling or feature representation Text understanding (LLMs, embeddings, document understanding) Graph learning (GNNs, message passing, topology-aware modeling) Visual modalities (2D/3D) Strong hands-on experience with Py Torch, custom model architectures, and efficient training/finetuning methods Ability to design clean, rigorous experiments (baselines, ablations, evaluation protocols) and communicate findings clearly Solid engineering discipline: Git, PRs, code reviews, reproducibility, experiment tracking, and collaborative development practices Preferred Skills Interest or familiarity with engineering, energy, or physical systems — curiosity about real-world technical domains is a strong plus Exposure to simulation-based learning, physics-aware models, or neuro-symbolic approaches Comfortable moving between research and applied prototyping, turning ideas into working demos Contributions to open-source projects, workshops, or scientific publications What We Offer The opportunity to shape the next generation of multimodal AI systems for energy, industry and sustainability Access to rich, real-domain multimodal datasets, rarely available in academic or tech environments A role at the intersection of AI research, physical systems understanding and sustainability, working on problems with real impact A fast moving, collaborative, and deeply technical team, embedded within Schneider Electric’s global AI strategy and innovation ecosystem Looking to make an IMPACT with your career? When you are thinking about joining a new team, culture matters. At Schneider Electric, our values and behaviors are the foundation for creating a great culture to support business success. We believe that our IMPACT values – Inclusion, Mastery, Purpose, Action, Curiosity, Teamwork – starts with us. IMPACT is also your invitation to join Schneider Electric where you can contribute to turning sustainability ambition into actions, no matter what role you play. It is a call to connect your career with the ambition of achieving a more resilient, efficient, and sustainable world. We are looking for IMPACT Makers; exceptional people who turn sustainability ambitions into actions at the intersection of automation, electrification, and digitization. We celebrate IMPACT Makers and believe everyone has the potential to be one. Become an IMPACT Maker with Schneider Electric – apply today! €36 billion global revenue +13% organic growth 150 000+ employees in 100+ countries #1 on the Global 100 World’s most sustainable corporations You must submit an online application to be considered for any position with us. This position will be posted until filled. Schneider Electric aspires to be the most inclusive and caring company in the world, by providing equitable opportunities to everyone, everywhere, and ensuring all employees feel uniquely valued and safe to contribute their best. We mirror the diversity of the communities in which we operate, and ‘inclusion’ is one of our core values. We believe our differences make us stronger as a company and as individuals and we are committed to championing inclusivity in everything we do. At Schneider Electric, we uphold the highest standards of ethics and compliance, and we believe that trust is a foundational value. Our Trust Charter is our Code of Conduct and demonstrates our commitment to ethics, safety, sustainability, quality and cybersecurity, underpinning every aspect of our business and our willingness to behave and respond respectfully and in good faith to all our stakeholders. You can find out more about our Trust Charter here Schneider Electric is an Equal Opportunity Employer. It is our policy to provide equal employment and advancement opportunities in the areas of recruiting, hiring, training, transferring, and promoting all qualified individuals regardless of race, religion, color, gender, disability, national origin, ancestry, age, military status, sexual orientation, marital status, or any other legally protected characteristic or conduct.
At Schneider Electric, we are committed to solving real-world problems to create a sustainable, digitized, new electric future. Artificial Intelligence has the potential to transform industries and help unlock efficiency and sustainability. Within our Global AI Hub we combine our long-standing manufacturing and domain expertise with cutting-edge innovation in AI, machine learning, and deep learning to empower smarter decision-making, agility, and decarbonization. Our Strategy & Innovation team drives the AI strategy and innovation efforts for the AI Hub, Schneider Digital, and Schneider Electric at large. We are building the next generation of intelligent systems that combine large-scale multimodal models, graph/topology understanding, simulation, and domain logic to enable system-level reasoning across energy, buildings, industry, and data centers. Your role : We’re looking for a curious, fast-moving applied research scientist who loves turning cutting-edge papers into prototypes and pushing them further. You combine strong transformer fundamentals with rigorous experimentation, solid engineering habits, and an end-to-end maker mindset - from preparing the data to building the model to crafting demos that make the value visible. You thrive in a collaborative environment, engage actively with the research community, and enjoy working with product and business teams to translate ideas into real impact. Your responsibilities : Develop advanced representations for core modalities — time series, tabular, text, and graph/topology, visual/3D data Rapidly translate state-of-the-art research into prototypes, adapting multimodal and transformer-based architectures to Schneider-specific datasets Build robust, reproducible ML pipelines, covering data preparation, experiment tracking, baselines, ablations Lead the creation and preparation of multimodal datasets, transforming raw data (such as time-series signals, structured tables, documents, diagrams, and system relationships) into clean, usable training datasets Collaborate with domain experts and product teams to align modeling choices with physical constraints and convert prototypes into clear, impactful demonstrations
Your profile : Required Qualifications PhD in Machine Learning, AI, Computer Vision, NLP, Robotics, or related field with strong foundations in transformers and modern representation learning. We are also open to exceptional candidates from top Master’s programs or leading engineering schools with demonstrated research or applied excellence Demonstrated experience in multimodal ML, with strong skills in at least two core modalities: Time-series modeling (e.g., forecasting, anomaly detection, foundation models) Tabular/structured data modeling or feature representation Text understanding (LLMs, embeddings, document understanding) Graph learning (GNNs, message passing, topology-aware modeling) Visual modalities (2D/3D) Strong hands-on experience with Py Torch, custom model architectures, and efficient training/finetuning methods Ability to design clean, rigorous experiments (baselines, ablations, evaluation protocols) and communicate findings clearly Solid engineering discipline: Git, PRs, code reviews, reproducibility, experiment tracking, and collaborative development practices Preferred Skills Interest or familiarity with engineering, energy, or physical systems — curiosity about real-world technical domains is a strong plus Exposure to simulation-based learning, physics-aware models, or neuro-symbolic approaches Comfortable moving between research and applied prototyping, turning ideas into working demos Contributions to open-source projects, workshops, or scientific publications What We Offer The opportunity to shape the next generation of multimodal AI systems for energy, industry and sustainability Access to rich, real-domain multimodal datasets, rarely available in academic or tech environments A role at the intersection of AI research, physical systems understanding and sustainability, working on problems with real impact A fast moving, collaborative, and deeply technical team, embedded within Schneider Electric’s global AI strategy and innovation ecosystem