About
Our Mission
Founded in 2022, Keeling Labs was started as a place to develop and apply machine learning to solve the world's biggest problem-climate change. Our current priority is getting the grid to run on 100% clean energy, which is currently limited by battery storage (specifically, the algorithms that control them).
We're redefining these algorithms to unlock gigawatts of untapped energy storage capacity, enabling the grid to run on more clean energy from wind and solar. You can learn more about us here: Our Work Company Writing Code for a Cleaner Grid Progress and Traction
Since 2022, We
Went through Y Combinator (W23 batch) Built our first ML model for energy trading, which is a proving ground for our battery optimization problem (learn more here) Achieved regulatory certification as a grid participant in California (CAISO) in fall of 2023 Raised a $3M seed round to bring that model to a real electricity market Expanded the team Successfully deployed our model to trade energy in California in 2024 We're live in the grid, earning revenue with our machine learning model, and gearing up for growth.
What's Next in 2025
With our core tech validated in a real market, we're now laser focused on two things: Scaling our ML-based energy trading to more grid markets in the U.S. (we're in 1 of 7 ISOs) Building our larger, more complex model to operate giant physical batteries in the grid (learn more here)
To do this, we're looking to expand the team and bring on ambitious, mission-driven engineers that want to make a serious difference in the climate change problem with their work. The code you write at Keeling Labs will directly impact emissions, control physical infrastructure, and help scale climate solution.
About The Role
We're hiring for an ambitious, experienced machine learning engineer to help us scale our technology and impact in the grid. We're looking for someone with experience developing and deploying real-world ML in production applications-ideally in energy, automative, aerospace, self-driving, or other physical applications.
Overall, you'll be a Swiss Army Knife across the entire ML stack at Keeling Labs.
What You'll Be Responsible For
Solve challenging problems to bridge ML theory and real-world application Build efficient simulation environments for reinforcement learning (RL) models Optimize training & inference runtime, performance, and cost Work with our researchers to implement new ideas to improve our ML models Develop profiling and monitoring tools to oversee production performance Requirements:
3+ years experience applying ML to physical, real-world applications in a production environment Strong coding background (Python/PySpark/Terraform/JAX or other ML frameworks) Experience building training architectures on cloud / strong overall cloud background (AWS) Strong problem-solving abilities in the ML space B.S., MSc, or PhD in engineering, physics, or computer science (or equivalent industry experience) Mission-driven, collaborative attitude
Benefits
We offer full health, dental, and vision insurance to all employees, along with unlimited PTO.
Nice-to-have skills
- Machine Learning
- Python
- PySpark
- Terraform
- AWS
- California, United States
Work experience
Languages
