Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co.

We are an in-office company, and our expectation is that full-time employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. This in-office expectation does not apply to contractor positions

About the role

Our Localization, Calibration, and Mapping team delivers high-integrity solutions that let autonomous systems navigate with precision in real-time, safety-critical environments — across consumer automotive, trucking, mining, and construction. As a new team focused on platformization, we offer a rare opportunity to own core work leveraged across the entire organization.

You'll build the self-service platform that turns sensor calibration from an expert-dependent process into production infrastructure: cloud workflow orchestration, automated data-health gates, and tooling every autonomy program can run for itself. You'll get there by living in the current system first — onboarding new vehicle types, so what you build is shaped by real-world data and telemetry. We encourage engineers to take ownership of technical and product decisions and to interact closely with users to collect feedback.

At Applied Intuition, you will

Own calibration across a growing multi-platform fleet: onboard new vehicle types, root-cause production failures, and convert what you learn into reusable workflows

Drive cross-team work that raises the reliability of the entire calibration path — partner with build, hardware, and infrastructure teams to trace failures to their source

Build and operate cloud workflow orchestration for calibration at fleet scale, from data collection through evaluation and deployment

Design automated data-health gates that catch bad IMU/INS, GNSS/RTK, lidar, and camera data before it reaches the calibration path

Ship production-quality tooling that non-expert internal users can run themselves

Debug across the cloud/vehicle boundary — tracing root causes through orchestration and application logs one day, verifying how a sensor is actually wired the next

We're looking for someone who has

A track record of driving technical work across team boundaries: comfortable raising problems with the teams that own them, building agreement on systemic fixes, and following through without formal authority

Bachelors or Masters degree in Computer Science, Computer Engineering, or related field

4+ years building and operating production software systems, with strong Python and modern C++

Demonstrated ownership of a pipeline, platform, or internal tool that other teams depended on

Hands-on depth with a cloud workflow orchestration framework (Flyte preferred; Airflow, Argo, etc.), plus CI/CD, containerization, and data pipelines over large binary or log data

Strength in debugging systems from logs when the surface symptom is misleading

Enough sensor and robotics data literacy to reason about validity: what good IMU/INS, GNSS/RTK, lidar, and camera data looks like, and how to design a check that catches bad data