Lead Data Engineer

About Keeling Labs

Who We Are: We’re an applied ML research company squarely focused on solving climate change.

• We recently closed a $1.5M seed round

• We’re backed by Y Combinator (W23)

• Our founder previously started the Battery Data Science Team at Rivian

What We’re Building: We’re optimizing how large batteries in the grid buy and sell energy so that the grid can run on more renewables. To do this, we’re developing self-optimizing, self-adapting systems using reinforcement learning.

Why It Matters: As the grid increasingly shifts to renewable energy from wind and solar, more and more large battery systems are needed to store that energy for times when there’s huge demand for energy but not enough supply. As a society, we have all the physical battery technology needed to do this, but the software technology that figures out when and how to optimally use the battery is still in its infancy.

There’s going to be a 15x increase in these large batteries by 2030, and they’re currently growing at 50% YoY. As the grid is fundamentally altered by the addition of these batteries, we need to ensure that we’re utilizing all of them to their full potential.

Our Culture:

• Mission Focused: Solving climate change is both a massive problem and a serious problem. We’re looking for engineers that understand the magnitude of the situation, believe that we can solve it with technology, and want to play a leading role in that solution

• First Principles: We distill the problems we’re solving into their fundamental components, developing original technology to solve new issues and leveraging existing technology to scale and accelerate our impact

• Open-Source: We build on open-source frameworks, avoid vendor lock-in, and share knowledge with the wider development community that we’ve all benefitted immensely from

• Scout Mindset: We’re always seeking the right answer, celebrating opportunities where we’ve proven ourselves wrong or changed our minds

• In-Person: We’re building Keeling Labs as an in-person company! It’s hard to replace the communication, alignment, and brain-storming sessions that go along with being in-person, especially in the early days

About the Role:

Real-time systems that control batteries in the grid, next-generation ML training architecture, and continuously running data pipelines — We’re looking for an innovative, methodical data engineer that wants to design and build these systems from scratch.

You’ll be working in a fast-paced, learning-filled environment to build and expand our core data systems.

What You’ll Be Responsible For:

• Plan, build, and scale core data infrastructure and pipelines

• Develop distributed ML training systems

• Build CI/CD deployments for production systems

• Integrate grid data from multiples locations across the U.S.

Requirements:

• 3-5+ years in industry deploying production data systems

• Frameworks: Kubernetes, Spark, CI/CD, Git, Linux, Docker

• Languages: Python, PySpark, Terraform

• Cloud: AWS