Software Engineer - Calibration

Applied Intuition
Sunnyvale, California, United StatesPosted 26 March 2026

Tech Stack

Job Description

About Applied Intuition 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 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. About the role We are looking for a software engineer with expertise in calibration systems for autonomous vehicles or mobile robots. Your contributions will focus on designing and building a calibration pipeline for a growing fleet of vehicles. You will contribute towards a critical foundational piece of our AV program by ensuring that every vehicle is able to leverage a multi-sensor, multi-modal representation of the world to navigate through it. In this role you will exercise engineering excellence to unlock both developer and production workflows at scale. In addition to your engineering contributions, by working in our dynamic and customer-focused team culture, you will contribute to and learn from best practices in the nascent autonomy industry. We move fast and we focus on excellence, for our products and for our business. If you are hands-on and looking for a place to have a multiplying effect on making autonomous systems a reality, Applied is the place for you! At Applied Intuition, you will: Implement a software pipeline which enables calibration of sensor intrinsic and extrinsic parameters for a variety of vehicles of different sensor configurations Design processes to manage the lifecycle and deployment of calibrations besides operations around data collection, processing and evaluation Work across teams, interface closely with and contribute to the core calibration algorithm team at Applied Have an opportunity to build state-of-the-art algorithms for both offline calibration in the factory / lab and online calibration to account for sensor variation due to temperature or other on-road and off-road conditions Enable sensor fusion and work with a variety of sensors including Camera, Lidar, Radar, IMU, GNSS, and more Drive an excellent product experience by designing a user-friendly Calibration procedure, as well as exposure of online Calibration status through HMI integration We're looking for someone who has: 2+ years of experience building software components or (sub) systems that address practical engineering challenges Hands-on experience with one or more domain relevant algorithm, software framework or tools, such as calibration, middleware, benchmarking suites, data sets and related pipelines, or algorithmic libraries C++ and/or Python programming expertise Willingness to learn and be a self starter, and can quickly become comfortable with new technical tools Passion for turning their software development expertise into solving real-world applications of autonomous system Nice to have: MSc in calibration, state-estimation, optimization, or closely related field Understanding of the core calibration concepts, ... (truncated, view full listing at source)
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