Senior Machine Learning Engineer

About AirGarage

AirGarage is on a mission to bring real estate online, starting with parking.

We replace broken parking machines, fragmented software, and manual, labor-intensive operations with a unified, data-rich operating system for parking real estate. We handle everything it takes to run and optimize a parking asset: payments, dynamic pricing, enforcement, license plate recognition, analytics, and more.

By building all of our technology in-house, we are able to deliver a magical experience for drivers while providing real-time visibility and revenue increases of 20-50% or more for real estate owners. That’s why national real‑estate leaders like Hines and Greystar, as well as technology companies like Meta, partner with AirGarage to optimize their parking facilities.

AirGarage uses datapoints like real-time occupancy, local events, weather, driver behavior, competitor pricing, and more to bring true intelligence to real estate owners’ assets for the first time.

We’re investing aggressively to make the physical world legible to a digital system: cameras, sensors, and software that generate a firehose of real-time data about the world around us. That data fuels models and algorithms that allow us to optimize performance at each property while giving owners the clarity and control they’ve never had before.

Before you can optimize an asset, you need to observe it. Before you can observe it, you need to bring it online.

We are starting with the $131 billion US parking real estate market because it is one of the most offline and mismanaged commercial real estate asset types. 26% of the land area in the median American urban core is dedicated to parking.

We are backed by top tier investors including Headline Growth, Andreessen Horowitz, Floodgate, Founders Fund, Abstract Ventures, and angel investors who have founded or worked at companies like Uber, Opendoor, Flexport, and more.

Want to learn more about AirGarage and the problem we're tackling?

Check out these podcasts:
https://www.youtube.com/watch?v=AU0NkDK51E4
https://youtu.be/_8aM6NQHYiE?si=p5WIujBWUA1sG-b7

THE ROLE 👨‍💻

We’re looking for a Senior Machine Learning Engineer to lead impactful projects in machine learning and software engineering across our platform. You’ll enhance our in-house License Plate Recognition (LPR) system, introduce entirely new systems, and advance our data-driven dynamic pricing and enforcement platforms. Your role involves developing efficient, practical machine learning models optimized for both edge devices and cloud deployments, as well as identifying when traditional algorithms are more effective than ML solutions. Beyond the models and algorithms, you’ll contribute to building the supporting systems by creating scalable backend systems for data ingestion, processing, and analytics. This role requires a versatile engineer who prioritizes pragmatic, effective solutions over simple one-size-fits-all approaches.

As the first dedicated machine learning hire, this is a foundational role with the opportunity to make high-impact technical decisions and establish technical best practices. This is a high-leverage role with visibility across the business and plenty of room to grow.

WHAT YOU WILL DO 🚀

• Develop, deploy, and optimize machine learning models, with applications spanning computer vision, dynamic pricing, and operational intelligence.

• Design and implement scalable backend systems for ingesting, processing, and analyzing large datasets.

• Collaborate closely with other engineers to build the necessary infrastructure for deploying models into production environments.

• Identify pragmatic opportunities for applying ML/AI, prioritizing real-world impact over hype.

• Ensure the robustness, efficiency, and maintainability of our ML models and related software systems.

• Conduct thorough code reviews, mentor teammates, and raise the engineering quality bar.

• Work daily with product, operations, and founders to ship high‑impact features quickly.

• Drive continuous improvement in tooling, processes, and developer experience.

WHAT YOU NEED 🧠

• 4+ years of professional experience in applied machine learning engineering, including model training, deployment, and optimization.

• Strong proficiency in Python and experience with machine learning frameworks such as PyTorch, TensorFlow, or similar.

• Demonstrated expertise applying computer vision algorithms and t