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 a more sustainable and efficient power grid.

The position offers an opportunity to work on transformative projects in the energy sector, developing AI solutions for critical infrastructure. 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 proficiency in programming languages such as Python. A Master's or PhD in a relevant field is required, along with substantial experience in the energy or industrial automation sectors.

Key responsibilities include leading the development of AI/ML models, creating analytics for grid system optimization, implementing MLOps practices, and ensuring seamless integration of AI solutions into both cloud and edge environments. The role combines technical leadership with hands-on development, requiring both deep technical knowledge and strong collaborative skills.

GE Vernova offers a collaborative environment where innovation is valued, with opportunities to work on projects that directly impact the future of energy. The company provides competitive benefits, including private health insurance, development opportunities, and flexible work arrangements. This role represents a unique opportunity to contribute to the global energy transition while working with cutting-edge technology.