Lead Computer Vision Solution Architect
New
C
ClariosAutomotive Manufacturing
Bulgaria, Georgia, Lithuania, Mexico, Moldova, Poland, UkraineFull-TimeLead
Salary not disclosed
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Job Details
- Experience
- Experienced
- Required Skills
- PythonKubernetesMachine LearningOpenCVPyTorchC++AzureTensorflowMLOpsComputer Vision
Requirements
- Proven experience designing and delivering production-grade computer vision solutions.
- Strong knowledge of computer vision architecture, model development, and real-time inference.
- Experience taking computer vision solutions from proof of concept through production deployment and ongoing support.
- Experience designing scalable and repeatable platforms for deployment across manufacturing plants and production lines.
- Experience designing solutions that integrate cameras, edge devices, on-premises infrastructure, cloud services, and enterprise applications.
- Experience integrating computer vision solutions with manufacturing equipment and operational systems.
- Ability to assess camera placement, lighting, image quality, hardware, latency, and environmental requirements.
- Experience establishing MLOps practices, including model testing, deployment, monitoring, versioning, and retraining.
- Strong software architecture and systems integration expertise.
- Understanding of manufacturing operations and Overall Equipment Effectiveness, including availability, performance, and quality.
- Ability to translate business and manufacturing challenges into scalable technical solutions.
- Hands-on technical leadership experience, including solution design, prototyping, technical reviews, troubleshooting, and guidance for engineers, developers, and data scientists.
Responsibilities
- Lead the architecture and hands-on development of a scalable computer vision platform for manufacturing environments.
- Define a repeatable and configurable solution architecture that can support deployment across more than 50 global plants.
- Balance the requirements of initial manufacturing use cases with the long-term scalability, maintainability, and supportability of the platform.
- Design the platform to accommodate differences in plant equipment, production processes, camera configurations, networking, security, and local infrastructure.
- Provide technical leadership and guide implementation decisions throughout the full solution lifecycle, from discovery and prototyping to production deployment.
- Collaborate with business and technology stakeholders, plant personnel, product leadership, data scientists, computer vision engineers, software developers, and infrastructure teams.
- Develop technical prototypes where needed, conduct architecture and implementation reviews, and troubleshoot complex technical issues.
- Ensure consistency of the core platform architecture and deployment approach across different plant environments.
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