AI / ML Engineer
Company: E Source
Location: Location not specified (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-04-30
About this role
At E Source, we help utilities make sense of complexity in a rapidly changing landscape, and we’re looking for an AI / ML Engineer to help shape how that impact shows up in the world.
E Source is a research, data/analytics, and technology focused professional services firm focused exclusively on the utility industry in the US and Canada. We help utilities target and serve their customers more effectively, enhance and optimize their grid, and leverage operating best practices and technologies to manage their business more effectively. Headquartered in Texas, we have 450+ employees across the US and Canada. Learn more at www.esource.com
Joining E Source as a Senior AI/ML Engineer is an exciting opportunity to work with a dynamic and talented team, leveraging your skills to drive meaningful impact in the utility industry. You’ll contribute to the next generation of AI and ML solutions that blend predictive modeling, optimization, and generative reasoning to empower sustainable decisions.
If you are a self-motivated engineer who thrives in a collaborative, innovative environment, and if you’re passionate about building intelligent, scalable AI/ML systems, we invite you to apply and help shape the future of utilities.
As a Senior AI/ML Engineer at E Source, you’ll play a crucial role in our machine learning engineering team. Collaborating with data scientists and software engineers, you’ll contribute to the development of cutting-edge ML and AI products that support our mission of building a sustainable future with utilities.
Your expertise will be instrumental in building tools and pipelines for developing and scaling machine-learning models, including emerging AI system design components and agentic architectures. You’ll work across a range of use cases—like electrification, network reliability, geospatial analysis, time series forecasting, image and text processing, and AI-driven decision systems—using both traditional ML and modern gener...