Machine Learning Engineer – AI for Grid Innovation & Energy Transition

GE Vernova is seeking a Machine Learning Engineer to join their AI & Grid Innovation team, focusing on developing and deploying cutting-edge AI/ML models for grid innovation applications. This role sits at the intersection of artificial intelligence and energy systems, working to accelerate the transition to more sustainable and efficient power grids.

The position offers an opportunity to work on transformative projects in the energy sector, developing AI solutions that will help electrify and decarbonize the world. Reporting to the AI Director within the CTO organization, you'll collaborate with Grid Automation product lines, R&D teams, and other business units to create impactful solutions across energy systems, smart infrastructure, and industrial automation.

The ideal candidate will bring strong technical expertise in machine learning, with experience in frameworks like TensorFlow, PyTorch, and scikit-learn, along with practical knowledge of deploying ML models in production environments. You'll need to understand both the technical aspects of AI/ML and their practical applications in the energy sector.

Key focus areas include predictive maintenance, load forecasting, and system optimization, requiring both technical depth and business acumen. The role demands expertise in MLOps, cloud platforms, and programming languages like Python, while emphasizing collaboration and communication skills.

GE Vernova offers a collaborative environment where innovation is valued and contributions make tangible impact. The company provides competitive benefits, including private health insurance, and emphasizes professional development. This role represents an opportunity to be at the forefront of the energy transition, working with advanced grid technologies and contributing to a more sustainable future.