A global AIoT software leader in Net Zero, Univers is committed to becoming the world's leading net zero technology partner for enterprises, governments, and cities to accelerate progress and improve their citizens quality of life.

EnOS™, Univers proprietary AIoT operating system, connects and manages more than 220 million smart devices and 800 gigawatts of energy assets globally. Univers growing ecosystem of more than 360 customers and partners spans 10 industries and includes Accenture, Amazon Web Services, GovTech Singapore, IBM, Keppel Corporation, Microsoft, Nissan, PTT, Solarvest, Total and ST Engineering. The company has close to 900 employees and 12 offices across the United Kingdom, France, Germany, the Netherlands, Norway, Japan, Thailand, China, and the United States, with headquarters in Singapore.

For more information, please visit https://univers.com/

Job Title: AI Grid Engineer

Job Summary:

The AI Grid Engineer will be a key member of the Smart Grid Centre of Excellence, responsible for the research, development and delivery in Smart Grid software initiatives. This role focuses on the optimization of smart grid projects, with a strong emphasis on research, industry collaboration, and advanced technology adoption. The ideal candidate will combine deep domain expertise with customer-facing capabilities to ensure the successful delivery of smart grid solutions.

Responsibilities:

Research and Innovation:

Conduct research on emerging trends and technologies in the AI Grid sector.
Develop innovative solutions to improve AI Grid software efficiency and reduce costs.
Publish technical papers and participate in conferences to represent the Centre's expertise in AI grid.

Collaboration and Training:

Work closely with cross-functional teams to support AI Grid software initiatives.
Build partnerships with academic institutions, industry leaders, and governmental agencies to foster innovation and knowledge exchange.

Policy and Compliance:

Stay updated on global and regional regulations affecting AI Grid software development.

Qualifications & Experience:

Master's/Ph.D. in Electrical Engineering, or Computer Science and Engineering or a related field.
Deep understanding of AI Grid technologies, system integration, and grid dynamics.
Related research experience on Artificial Intelligence/Machine Learning for energy systems
Excellent communication and interpersonal skills.
First-author papers in IEEE Transactions, PSCC, CIGRE, NeurIPS workshops, etc.