AI Vision Engineer building production computer vision and multimodal AI systems for heavy industries at Nexxa. Deploying real-time models across edge devices and cloud environments.
Responsibilities
Design, train, evaluate, and deploy computer vision models for real-world industrial applications
Build and optimize computer vision pipelines for object detection, segmentation, classification, OCR, tracking, and visual understanding
Develop and fine-tune vision-language models for multimodal reasoning, visual question answering, and document understanding
Design and optimize real-time inference pipelines for edge devices and cloud deployment
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
Develop evaluation frameworks and benchmarks measuring accuracy, robustness, latency, and business impact
Optimize models using 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 computer vision, multimodal AI, and autonomous systems advancements
Requirements
Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, Statistics, Artificial Intelligence, or a related technical field, or equivalent practical experience
3+ years of industry experience in Computer Vision, Machine Learning, Applied AI, or related fields
Demonstrated experience independently owning and delivering computer vision projects from concept to production
Strong programming skills in Python
Hands-on experience with PyTorch and modern deep learning workflows
Experience developing and deploying computer vision models for detection, segmentation, classification, and OCR in production environments
Experience with image and video processing libraries such as OpenCV
Experience with common CV/detection frameworks such as YOLO, Detectron2, or MMDetection
Experience working with VLMs, multimodal models, or Generative AI applications
Strong understanding of machine learning fundamentals, model evaluation, experimentation, and model deployment
Experience working with Hugging Face Transformers and open-source AI ecosystems
Familiarity with data annotation workflows, dataset curation, hyperparameter optimization, and inference optimization
Experience building production-grade software and AI systems
Master's degree in a related field is preferred
Preferred experience with OCR, document understanding, visual reasoning, 3D vision, SLAM, sensor fusion, TensorRT, ONNX Runtime, quantization, pruning, edge hardware, LangChain, LangGraph, vector databases, AWS, GCP, Docker, Kubernetes, MLOps, PostgreSQL, distributed training, model serving, open-source contributions, and startup or high-growth environments
Benefits
Significant opportunities for career development and advancement
Competitive compensation package
Equity package reflective of expertise and contributions
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