Design, develop, and maintain software systems for vehicle identification and tracking using cameras.
Prototype advanced algorithms in Python and implement/optimize them for real‑time applications using C++ or Rust to ensure high-performance data processing.
Leverage computer vision, machine learning, and signal processing methodologies to improve anomaly detection and pattern recognition in video and sensor streams.
Ensure system reliability, safety, and performance under real-world conditions.
Collaborate with cross‑functional teams (AI/ML, robotics, embedded systems, UX) to integrate end‑to‑end solutions.
Lead architectural decisions and enforce best practices in scalability, security, and maintainability.
Stay updated with the latest advancements in computer vision, machine learning, and software development, applying innovative solutions to maintain our technological edge.
Mentor junior developers and contribute to code reviews and technical guidance.
At Copernicus Autonomous Control Systems GmbH , a wholly owned subsidiary of Ford Motor Company, we are shaping the future of intelligent mobility through advanced autonomous driving and infrastructure-based control systems .
Building on deep expertise in automated vehicle movement, we develop cutting‑edge solutions that enable autonomous valet parking and maneuvering in complex real‑world environments such as parking facilities, logistics hubs, and industrial sites. Our approach focuses on shifting intelligence from the vehicle to the surrounding infrastructure—leveraging AI, computer vision, and connected systems to orchestrate safe, precise, and efficient vehicle operations.
As part of Ford’s global innovation ecosystem, we play a key role in advancing Level 4 autonomous capabilities , delivering scalable and cost‑effective solutions that enhance safety, optimize space utilization, and significantly improve user experience.
Driven by a commitment to innovation, reliability, and safety, Copernicus Autonomous Control Systems GmbH is dedicated to enabling a future where vehicles move seamlessly and autonomously within smart environments—making parking and low‑speed vehicle operations effortless and intelligent.
#J-18808-LjbffrVeröffentlichungsdatum:
02 Mai 2026Standort:
Brandenburg an der HavelTyp:
VollzeitArbeitsmodell:
Vor OrtKategorie:
Erfahrung:
2+ yearsArbeitsverhältnis:
Angestellt
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