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:

1. Scaling our ML-based energy trading to more grid markets in the U.S. (we're in 1 of 7 ISOs)

2. 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:

• Research and implement new ideas to improve our ML models

• Solve challenging problems to bridge ML theory and real-world application

• Optimize training & inference runtime, performance, and cost

• 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 problem-solving abilities in the ML space

• Experience with multiple of Reinforcement Learning, Recurrent Neural Networks, Graph Neural Networks, Time-Series Forecasting, Supervised Learning

• Strong experience with advanced training architectures on cloud

• B.S., MSc, or PhD in engineering, physics, or computer science (or equivalent industry experience)

• Strong coding experience with JAX or another leading ML framework in Python

• Mission-driven, collaborative attitude

Benefits:

We offer full health, dental, and vision insurance to all employees, along with unlimited PTO.

Phone Screen (Background, Overview) → First Round (Technical) → Second Round (Full Team, Technical + Culture) → On-Site → Offer