Siemens Energy, Inc. is looking to solve critical challenges related to grid modernization, renewable energy acceleration, and climate change mitigation by developing next-generation foundation models for power grid & substation applications.
Requirements
- 5 or more years of research experience in Deep Learning, Machine Learning, or related areas, with a focus on developing and scaling innovative AI solutions.
- Experience building foundation models and related concepts, with direct prior experience in at least one of the following AI for Simulation/AI for Physics, Neural Operators, GNNs (Graph Neural Networks), Transformers
- Proven ability to design, develop, and implement novel deep learning architectures and algorithms
- Experience scaling solutions involving large datasets and complex models, utilizing large compute clusters
- Strong ability to work independently, rapidly iterate on ideas, and quickly develop and validate proof-of-concepts
- Publications in top-tier AI conferences and journals, contributions to open-source machine learning projects, and/or prior experience in a top AI research lab
- Experience applying AI/ML to power systems, electrical grids, or related domains
Responsibilities
- Conducting original, high-impact research in foundation models, specifically tailored for power grid data modalities and applications, and spearheading the development of novel deep learning architectures, algorithms, and training methodologies tailored for these
- Deeply investigating and advancing state-of-the-art research in relevant areas, adapting and integrating methods and techniques from public research
- Collaborating closely with AI engineers and domain experts to translate research breakthroughs into practical, scalable solutions deployable within real-world power grid systems
- Building and mentoring a high-performing research team, fostering a collaborative and innovative research culture within the newly formed AI lab, and driving rapid iteration and proof-of-concept (PoC) development to quickly validate research ideas
- Communicating research findings effectively to both technical and non-technical audiences (via technical blogs or publications in conferences and journals), and representing the lab externally at conferences and industry events
- Driving research projects forward independently, demonstrating strong initiative, problem-solving skills, and a results-oriented approach
Other
- Master's or Ph.D. in Computer Science, Electrical Engineering, Physics, Mathematics, or a related quantitative field
- Excellent communication, presentation, and teamwork skills, with the ability to lead and inspire a research team and collaborate effectively with diverse stakeholders
- Hybrid (Remote/Büro)
- Vollzeit
- Berufserfahrene
