About Enertel AI
Enertel uses graph neural networks to support our power grid forecasting products, all of which are the foundation for our newly released bidding optimization product. We use this software to support over 5GW of renewable energy generation. We work with real-time and day-ahead market data to deliver production-grade forecasts and automated bid strategies across ERCOT, CAISO, PJM, and beyond. Most of this workflow is already automated.
The Role
We’re hiring a software engineer to take full ownership over major components of our data integration infrastructure. You’ll contribute to both our machine learning data pipelines by extending existing templates to new sources of data, and help architect our bid automation systems.
This role is hands-on from day one: you’ll be submitting merge requests in your first week, deploying real infrastructure in your second, and owning critical subsystems by your first month.
The truth is, you don't need to know much about power markets to succeed in this role. You need to be great at coding, open to using generative AI in your workflows, and deal well with ambiguity. You'll be supported, but your hands won't be held along the way.
What You’ll Do
Collaborate with ML engineers (and potentially become one yourself) to improve forecast accuracy
Develop components of our bidding engine and integrate with downstream schedulers (e.g. QSEs)
Deploy and monitor services in production (Docker, Kubernetes, GCP)
Work closely with a 100% technical team on real-world systems with high uptime expectations
You Might Be a Fit If You
Thrive in fast-paced, high-autonomy environments and want to start your own company one day
Have experience with Python, cloud infrastructure, APIs, and data modelling
Have touched ML pipelines or forecasting models in production
Value clean code, merge early/merge often, and own what you ship
Want to work on meaningful problems in energy, AI, and infrastructure
Why Enertel?
Total ownership: you’ll lead, not just support
Your work hits production fast and drives real-world decisions
Remote-first with flexible hours
We know it's a bigger risk to avoid AI coding tools than to use it
We automate relentlessly, including our own workflows
