AI Research Scientist

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.

About the role

We’re looking for a curious, fast-moving applied AI research scientist (Official Title: Data Scientist) who loves working on cutting-edge innovation projects and transforming them into prototypes. You will drive the development of multimodal AI systems that power real-world energy and industrial decisions at scale. The right candidate will combine strong fundamentals in foundation models 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. 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.

Responsibilities

• Advance state-of-the-art research 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

Requirements

• PhD in Machine Learning, Artificial Intelligence, NLP, Robotics, or a related field, with strong foundations in transformers and modern representation learning. Candidates with a Master’s degree and a track record of outstanding research or applied impact are also encouraged to apply.
• Demonstrated experience in foundation models and post-training
• Strong hands-on experience with PyTorch, 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

Benefits

Our Total Rewards package outlines all the benefits and support you’ll enjoy as part of the Schneider Electric team:

• Care for Yourself and Your Family: Medical (with member reward points), dental, vision, and basic life insurance, Benefit Bucks, flexible work arrangements, paid family leaves, well-being programs, 12 holidays per year, and 15 days of paid time off per year.
• Invest and Plan Your Future: Competitive pay and programs including base salary, incentives, company share ownership, and 401(k) with match.
• Grow Your Skills and Career: Performance discussions, global opportunities, the Schneider Career Hub, and learning platforms like Coursera.
• Team Up in the Workplace: Collaboration, recognition, sharing your voice, and an inclusive workplace.
• Support Your Community: Volunteer leave, programs with the Schneider Electric Foundation, youth education initiatives, and military leave benefits.

Pay

For this U.S.-based position, the expected pay range is USD 117,600 - USD 176,400 per year. This pay range includes base pay and short-term incentives. The compensation range applies to candidates located within the United States. Individual pay is determined by several factors including performance, knowledge, job-related skills, experience, and relevant education or training.