Power Systems Research Engineer: ML-Driven Grid Optimization

Google LLC; San Francisco (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google DeepMind is seeking a Power Systems Research Engineer to advance optimization, data-driven methods, and scalable experiments for real-world grids. In this role you will ingest grid data, formulate AC/DC OPF and dispatch constraints for ML consumption, and collaborate with national laboratories, utilities, and internal teams to translate research into practical solutions.

Strong Python or Julia programming skills, deep systems knowledge, and excellence in communication are essential to

Qualifications

• 10 years of experience in Power Systems, Energy, or Power Plant Engineering.
• 2 years of leadership or people management experience.
• Experience with real grid operator data.
• Experience building power systems optimization models in Python or Julia.
• Experience in software engineering.

Responsibilities

• Ingest and curate real-world grid operator data.
• Formulate AC/DC Optimal Power Flow (AC-OPF), economic dispatch, and congestion management constraints for ML consumption.
• Serve as primary technical liaison with national laboratories (e.g., LLNL), utilities, grid operators, and internal teams.

Skills

Power Systems

Leadership

Grid data

Power optimization

Software engineering

Tools

Python

Julia

Job description

Google DeepMind is seeking a Power Systems Research Engineer to advance optimization, data-driven methods, and scalable experiments for real-world grids. In this role you will ingest grid data, formulate AC/DC OPF and dispatch constraints for ML consumption, and collaborate with national laboratories, utilities, and internal teams to translate research into practical solutions.

Strong Python or Julia programming skills, deep systems knowledge, and excellence in communication are essential to