AI Vision Engineer

Nexxa is building the best AI systems for heavy industries — enabling machines, systems and operations to think, decide and act autonomously across manufacturing, large-scale infrastructure, logistics and legacy environments.
Our mission is to translate deep technical breakthroughs into operational reality, solving some of the hardest systems-level problems in industry.

Role Overview

We are looking for an AI Vision Engineer to help design, build, and deploy next-generation computer vision systems across a diverse set of real-world industrial applications.

This role is ideal for someone with a strong foundation in Computer Vision and Machine Learning who is excited about working across the full vision stack, including classical and deep-learning-based CV, vision-language models (VLMs), multimodal reasoning, and real-time inference at the edge and in the cloud.

You will work closely with our AI and engineering teams to develop production-ready vision solutions, improve model performance, and help shape the next generation of intelligent visual systems.

What You'll Do

• Design, train, evaluate, and deploy computer vision models for real-world industrial applications.

• Build and optimize CV pipelines for tasks such as object detection, segmentation, classification, OCR, tracking, and visual understanding.

• Develop and fine-tune vision-language models (VLMs) for multimodal reasoning, visual question answering, and document understanding.

• Design and optimize real-time inference pipelines for deployment on edge devices and in the cloud.

• Build scalable data pipelines for image and video collection, annotation, augmentation, training, and evaluation.

• Fine-tune and evaluate open-source vision and multimodal foundation models using modern training and inference frameworks.

• Develop robust evaluation frameworks and benchmarks to measure model accuracy, robustness, latency, and business impact.

• Optimize models for production constraints, including quantization, pruning, and hardware-accelerated inference.

• Collaborate with product, engineering, and research teams to translate business requirements into technical vision solutions.

• Contribute to architecture decisions, technical design reviews, and AI/CV best practices.

• Stay current with the latest advancements in computer vision, multimodal AI, and autonomous systems.