Lead, Data Scientist / Research Engineer F/H

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 are looking for an applied research engineer with strong foundations in ML/AI and a deep interest in reasoning, agents, planning, and tool-augmented intelligence.

You will design novel reasoning architectures that combine foundation-model outputs with system structure, simulations, and domain rules - building prototypes that demonstrate robust, verifiable reasoning for real industrial systems.

Your responsibilities :



* Design novel reasoning methods that combine LLM/FM outputs with graphs, causal structure, and constraints to solve multi-step, system-level tasks


* Prototype agents/planners that can query tools (simulators, rule engines, optimizers) and self-check with constraints/physics before proposing actions


* Fuse multimodal signals - time-series, tabular, text, graph (vision/3D later)-into coherent world-state representations and uncertainty-aware decisions


* Establish evaluation for reasoning (task success, counterfactuals, causal sanity checks, safety/constraint satisfaction) and run clean ablations/baselines


* Collaborate with domain experts to encode topology, procedures, and invariants into the reasoning layer

Your profile :

Required Qualifications


* PhD in ML/AI/CS (or related) with strong grounding in transformers/LLMs and reasoning/representation learning.

We are also open to exceptional candidates from top Master's programs or leading engineering schools with demonstrated research or applied excellence


* 3+ years of industry experience applying ML/AI methods to real-world problems, including prototyping, experimentation, or integrating models into practical workflows


* Evidence of research in at least two of the following:
+ Causal & probabilistic modeling (interventions, counterfactuals, structure learning)
+ Graph/topology reasoning (GNNs, message passing, graph-of-thought)
+ Tool-augmented agents / planning (planning/search, tool calling, RAG for tools)
+ Physics/constraints-aware learning (PIML, rule integration, optimization under constraints)
+ Hands-on skill to turn...