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Multi-Sensor SLAM Fusion Navigation SW Engineer

Trimble · Höhenkirchen-Siegertsbrunn | 85635 | Deutschland · Hybrid, Onsite

Gehalt auf Anfrage

Gefunden am 15.05.2026

Match

84%

Fit in Skills, Kultur und Entwicklungspfad.

Beschreibung

Job Zusammenfassung In dieser Rolle entwickelst du Softwarearchitekturen für die Integration fortschrittlicher SLAM-Algorithmen mit LiDAR- und Kameradaten in Echtzeit-GNSS-Systeme, um innovative Navigationslösungen zu schaffen. Job Zusammenfassung In dieser Rolle entwickelst du Softwarearchitekturen für die Integration fortschrittlicher SLAM-Algorithmen mit LiDAR- und Kameradaten in Echtzeit-GNSS-Systeme, um innovative Navigationslösungen zu schaffen. Deine Rolle im Team Join Trimble's innovative multi-sensor team at our office in Höhenkirchen-Siegertsbrunn as a Multi-Sensor SLAM Sensor Fusion Navigation SW Engineer (m/f/d). Bring your ambition and dedication to advance real-time Aided Inertial Navigation Systems (AINS) technology by fusing it with SLAM based on LiDar and camera sensors. Your effort will focus on enhancing Trimble's precise GNSS positioning solutions by integrating advanced multi-sensor technology into the ProPoint engine. This role offers an exciting opportunity to contribute to both existing products and the development of next-generation solutions targeting a broad range of applications and use cases. In this software-development-focused role, you will define and develop the software architecture to implement state-of-the-art multi-modal Simultaneous Localization and Mapping (SLAM) algorithms based on LiDar and camera sensors and integrate them with GNSS/INS components on embedded systems. Define and develop a sustainable software architecture to implement state-of-the-art multi-modal Simultaneous Localization and Mapping (SLAM) algorithms based on LiDar and camera sensors. Implement the developed algorithms in C++ to run in real-time on embedded systems, test and verify. Define component-level interface requirements and collaborate with development teams to integrate other components. Manage the code base, releases and provide code reviews to peer developers. Utilize Matlab and/or Python for data analysis, visualization, and algorithm development. Contribute to IP protection efforts by documenting innovations and participating in patent filings. Unsere Erwartungen an dich Ausbildung Master's degree in Navigation, Aerospace, Robotics, Geodesy, or related engineering disciplines. Qualifikationen Proven track record in developing and deploying Simultaneous Localization and Mapping (SLAM) algorithms. Proven track record in developing C++ production code for real-time embedded systems in large code bases with strict release requirements. Strong analytical, problem-solving, and mathematical skills. Excellent communication skills and ability to discuss complex technical topics in English. Ability to work effectively as part of a development team with minimal supervision in a fast-paced development environment with changing priorities. Background in any of the following: Inertial sensing, AINS, Visual (-Inertial) Odometry, Lidar (-Inertial Odometry), sensor fusion, precise GNSS, real-time algorithms, and embedded systems. Familiarity with Jira or similar issue-tracking software. Erfahrung Experience in Matlab, Python or a comparable language. Experience with processing visual sensor data from LiDAR and cameras. Hands-on experience with optical sensors (specifications, calibration, prototyping). Experience with quality assurance and navigation system field applications. Themen mit denen du dich im Job beschäftigst AI Autonomous Driving Metadaten Level: Erfahren Job Feld: Application, Embedded Anstellung: Vollzeit Vertragsart: Unbefristetes Dienstverhältnis Arbeitsmodell: Hybrid, Onsite Unternehmenstyp: Etablierte Firma Branche: Industrie, Produktion Ort: Höhenkirchen-Siegertsbrunn | 85635 | Deutschland

Tech Stack

C++Python

Warum passt du zu dieser Stelle?

Fit technisch: Stark auf Backend und API-Architektur.

Gaps: Fehlende Tool-Erfahrung in 1-2 Schlüsselbereichen.

Success-Wahrscheinlichkeit: Hoch bei schneller Einarbeitung.