Software Engineer - Mapping and Localization

Applied Intuition
Stuttgart, Baden-Württemberg, GermanyPosted 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 mapping and localization for autonomous vehicles or mobile robots. Your contributions will focus on building mapping and localization solutions for autonomous and advanced driver-assistance use cases. You will be an early member of the fast-growing autonomy team in Stuttgart, which means you will have the opportunity to take broad responsibilities and impact the directions of the overall program. In addition to your engineering contributions, by working in our dynamic and customer-focused team culture, you will be a key contributor for a new business that builds on and informs best practices in the nascent autonomy industry. We move fast and 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: Design and implement a top-notch mapping and localization solutions, tailored for the use-cases at hand, running both on-road use on embedded ECUs and in the cloud Implement run-time-efficient in-vehicle SW for on automotive SOCs Build backend infrastructure for building, storing and processing of maps, both for use in ADAS/AD production-functions and for training ML models Apply automated techniques to generate maps from raw data, using and improving our internal tools for viewing and editing maps We're looking for someone who has: Passion for building a best-in-class mapping and localization systems that is absolutely reliable for demanding real-world environments MScin mapping, localization, or closely related field 3+ yrs of experience building software components or (sub) systems that address real-world mapping and localization challenges Hands-on experience with more than one domain relevant software framework or tools, such as middlewares, benchmarking suites, data sets and related pipelines, or algorithmic libraries Deep understanding of the core localization concepts, world representations and transforms, the intersection of mapping of localization, and error analysis and characterization Knowledge about how to analyze and compare the performance of various hardware solutions for localization C++ and/or Python programming expertise Nice to have: PhD in mapping, localization, or closely related field Deep hands-on expertise in relevant algorithms or methods, such as SLAM, probabilistic filtering, non-linear optimization, computational geometry, numerical analysis, or distributed systems Experience with large-scale data processing using frameworks Experience developing on automo ... (truncated, view full listing at source)
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