Computer Vision Engineer

Continental is a leading tire manufacturer and industry specialist. Founded in 1871, the company generated sales of €39.7 billion in 2024 and currently employs around 95,000 people in 54 countries and markets.

Tire solutions from the Tires group sector make mobility safer, smarter, and more sustainable. Its premium portfolio encompasses car, truck, bus, two-wheel, and specialty tires as well as smart solutions and services for fleets and tire retailers. Continental has been delivering top performance for more than 150 years and is one of the world’s largest tire manufacturers. In fiscal 2024, the Tires group sector generated sales of 13.9 billion euros. Continental's tire division employs more than 57,000 people worldwide and has 20 production and 16 development sites.

• Design, develop, deploy, and maintain computer vision solutions for automated inspection, defect detection, quality assurance, process monitoring, and manufacturing intelligence.
• Integrate vision applications with industrial cameras, lighting, controls, manufacturing execution environments, databases, and edge-computing platforms.
• Lead or support validation, commissioning, production rollout, user enablement, and operational support for plant-wide vision use cases.
• Monitor production performance and improve model robustness under changing products, equipment conditions, lighting, and process variation.
• Diagnose image-acquisition, camera-calibration, equipment-drift, and model-performance issues and drive sustainable corrective actions.
• Identify and prioritize new industrial vision opportunities, translating manufacturing pain points into deployable use cases with measurable operational impact.
• Evaluate emerging technologies such as deep-learning vision, multimodal AI, foundation vision models, and industrial vision platforms.
• Apply appropriate data, cybersecurity, model-risk, and responsible-AI controls throughout the solution lifecycle.

Computer vision and image processing, including model development, validation, performance measurement, and deployment.

• Python and relevant AI / vision frameworks; practical software deployment skills. Additional industrial programming capability is advantageous. Confidential | Prepared for compensation benchmarking purposes only
• Industrial cameras, optics, lighting, calibration, sensors, and edge-computing concepts.
• Industrial integration concepts, including PLC / controls, manufacturing systems, databases, APIs, and common connectivity protocols.
• Data analysis and visualization; structured problem solving using quality and root-cause methods.
• Project management, stakeholder communication, documentation, and change adoption in an operations environment.

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