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 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 expertise in machine learning, with experience in frameworks like TensorFlow, PyTorch, and scikit-learn, along with proficiency in programming languages such as Python. You'll be responsible for the full ML lifecycle, from design and development to deployment and optimization of models, working both in cloud and edge environments.

Key focus areas include predictive maintenance, load forecasting, and system optimization, all aimed at enhancing grid performance and reliability. The role requires both technical excellence and strong collaborative skills, as you'll be working closely with cross-functional teams to deliver AI-driven solutions that are efficient, equitable, and scalable.

GE Vernova offers a collaborative environment where expertise is valued and contributions make a tangible impact on the future of energy. The company provides competitive benefits, including private health insurance, development opportunities, and flexible work arrangements. This is an excellent opportunity for someone passionate about using AI to drive innovation in energy systems and contribute to the global energy transition.