Computer Vision Engineer
At a glance
Mid-level Machine Learning Engineering role at Continental. He Fei Shi · full-time.
Pay not stated Machine Learning Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build and run vision systems that inspect products, find defects, track processes and support manufacturing decisions
- Connect vision software to cameras, lighting, plant controls, manufacturing systems, databases and edge devices
- Help test, install and launch plant vision applications, then train users and support ongoing operations
- Track performance and diagnose image capture, calibration, equipment drift or model issues; make lasting fixes
- Turn manufacturing problems into measurable vision projects and assess newer AI methods and platforms
What you bring
- You have computer vision and image-processing skills spanning model building, validation, performance checks and deployment
- You can code in Python, use relevant AI or vision frameworks and deploy software in practice
- You understand industrial cameras, optics, lighting, calibration, sensors and edge-computing concepts
- You can work with industrial controls, manufacturing systems, databases, APIs and connectivity protocols
Who this fits
This mid-level, full-time role is based onsite in He Fei Shi. It suits someone who can bring computer vision into manufacturing operations and work through deployment, production support and collaboration with plant stakeholders.
From the employer
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.
Ready to drive with Continental? Take the first step and fill in the online application.