Company Background
Our client is a global leader in advanced energy storage solutions, specializing in the design and manufacturing of automotive batteries. Headquartered in Milwaukee, Wisconsin, the company serves major automakers and aftermarket retailers, producing over 150 million batteries annually and powering 1 in 3 vehicles worldwide. With operations in more than 50 countries, the company focuses on innovative and sustainable battery technologies for conventional, hybrid, and electric vehicles, supporting the evolving mobility ecosystem.
Project Description
The project focuses on building a strategic, scalable computer vision platform for manufacturing environments. The initial implementation will establish the core architecture and reusable capabilities needed to support a growing range of use cases and enable future deployment across a global network of production plants. The platform will help improve Overall Equipment Effectiveness by increasing visibility into production processes, identifying operational losses and inefficiencies, and generating actionable insights across equipment availability, performance, and product quality.
Technologies
Python, C++
OpenCV
PyTorch, TensorFlow
NVIDIA GPUs, NVIDIA Jetson, CUDA, TensorRT, DeepStream
ONNX, ONNX Runtime
REST APIs
Docker, Kubernetes
Microsoft Azure, AWS, Google Cloud Platform
IP and industrial cameras
OPC UA, MQTT, Modbus
Manufacturing systems: PLC, SCADA, MES, IoT, industrial historians
What You’ll Do
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;
Job 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 engi
