Senior Vision AI Engineer

About Proconex

Proconex is a trusted leader in industrial automation and process control solutions, proudly serving the industry for over 75 years. With a rich legacy of delivering high-performance systems and equipment to process industries—including oil & gas, chemicals, power, and life sciences—we are now entering an exciting new chapter. We are building on a solid foundation of over 10 years of successful deployments with our next generation of software products. Our software solutions are designed to empower industrial operators with operational analytics, enabling smarter, more efficient, and more reliable operations. This is a unique opportunity to be part of a growth-focused team that is taking proven technology to the next level.

About the Role

Linque is expanding its Vision AI and Cognitive Automation platform focused on applying real-time computer vision and AI to industrial, biopharmaceutical, and process manufacturing environments. We are seeking a Senior Vision AI Engineer to help lead the development, deployment, and customer-facing application of advanced vision AI solutions. This role sits at the intersection of deep technical execution, platform development, and real-world industrial use cases.

Key Responsibilities

• Design, develop, and deploy production-grade computer vision and machine learning models
• Build optimized end-to-end vision pipelines for real-time and near-real-time applications
• Translate complex industrial problems into scalable AI architecture
• Collaborate cross-functionally with product, engineering, and commercial teams
• Participate in technical customer discussions, pilots, and evaluations
• Support prototypes through pilot and production transitions
• Mentor junior engineers and contribute to technical best practices

Required Qualifications

• 5+ years’ experience in computer vision and machine learning
• Strong hands-on experience deploying AI systems in production
• Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, Keras)
• Deep knowledge of Video / Image processing tools (e.g. Mask R-CNN, ResNet, U-Net)
• Knowledge of object and anomaly detection (Autoencoders, FastFlow, Transformers)
• Tunning experience for CNNs and Vision Models (e.g., MLFlow, NVIDIA TAO, MMD, MMS)
• Mastery of model interchange and GPU acceleration (e.g. ONNX, CUDA, cuDNN)
• Experience working with image/video pipelines, container orchestration (local and cloud)
• Understanding of the full ML / AI lifecycle

Preferred Qualifications

• Experience with real-time vision systems
• Background in industrial automation or regulated environments
• Experience with edge or cloud deployment
• Ability to communicate complex technical topics clearly