Senior Leader – Vision Systems Engineering

The Senior Leader – Vision Systems Engineering plans, directs, and oversees the Electrical, Software, and Imaging AI Engineering teams supporting BWCS's Vision product lines. The role's central mandate is to modernize and consolidate several legacy inspection product lines into a single, unified product portfolio, built on a current software stack with GPU-accelerated AI at its core, to deliver the world's leading web inspection systems.

The position partners closely with engineering leadership and cross-functional leaders to align resources and execution with business strategy. It is structured as a development pathway to Director level within 2–3 years, with increasing ownership of strategy, budget, and organizational leadership.

• →Recruit, hire, onboard, and develop engineering staff across hardware, software, and imaging AI disciplines.
• →Build the next layer of technical leads and people managers.
• →Manage team workload, priorities, and engineering backlogs.
• →Provide timely, constructive performance evaluations and ensure compliance with BW policies and procedures.

• →Lead the consolidation of legacy vision product lines into a unified platform architecture, defining a common hardware, software, and AI foundation and a phased migration plan for the installed base.
• →Drive adoption of a modern software stack and GPU-driven AI model integration across the portfolio, replacing fragmented legacy codebases and rule-based inspection.
• →Own the technology roadmap and end-to-end system architecture: line-scan and area-scan cameras, optics, illumination, acquisition, compute, and integration with machine controls.
• →Direct development of AI-based defect detection, classification, and root-cause identification on films, nonwovens, paper, and printed substrates.
• →Establish disciplined processes for image data collection, labeling, model training, validation, deployment, and field performance monitoring.
• →Partner with Product and Project Management to prioritize work, allocate resources, and support cost analysis, resource planning, and schedules.
• →Ensure delivery within budget and against monthly financial and operational commitments.
• →Lead Design Reviews across vision hardware, software, and AI model development.
• →Manage design partners and vendors (camera, optics, lighting, GPU compute, AI tooling) for roadmap execution, obsolescence management, and order fulfillment.
• →Establish engineering standards, security practices, and development processes across the unified portfolio.
• →Partner with manufacturing, supply chain, and field service to support customer satisfaction and installed-base migration.
• →Provide technical expertise to executive leadership and customers; stay current on machine vision and industrial AI trends.
• →Perform other duties as assigned.

• Strong results orientation with a sense of urgency.
• Proven leadership of multi-disciplinary engineering teams.
• Track record consolidating or re-platforming multiple legacy products onto a common architecture.
• Excellent communication skills, including explaining technical trade-offs to executive and customer audiences.
• Expert knowledge of machine vision system design: cameras, optics, illumination, and industrial interfaces (GigE Vision, CoaXPress, Camera Link, GenICam).
• Proven delivery of web or substrate inspection systems for continuous processes.
• Deep expertise in imaging AI for industrial defect detection, including detection, segmentation, and anomaly detection models for limited-defect datasets.
• Hands-on experience with GPU-accelerated inference at production line speeds (CUDA, TensorRT, ONNX), plus OpenCV, PyTorch and/or TensorFlow, and YOLO.
• Software knowledge including C, C++, C#, Python, embedded, Windows, Linux, Git/GitHub; experience leading multi-developer projects using AI-assisted development.
• Systems integration experience with PLCs, HMIs, and industrial protocols (e.g., OPC UA, EtherNet/IP, Profinet).
• PCB design, layout, and test experience; Altium preferred.
• Strong organizational, prioritization, and problem-solving skills with a continuous learning mindset.

• Bachelor's degree in Electrical, Computer, or Software Engineering or related field required; Master's or PhD in Computer Vision, Machine Learning, or Image Processing preferred.
• Minimum of 12 years of relevant experience, including at least 5 years in industrial machine vision or inspection.
• Minimum of 5 years leading engineering teams, with demonstrated readiness for Director level (strategic planning, budget ownership, leading leaders).
• Proven ability to build team-oriented, high-performance environments.
• Knowledge of color theory and color measurement is a plus.
• Ability to travel occasionally, domestically and internationally.

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