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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Computer Vision / AI Engineer II - **Company:** VDart, Inc. - **Location:** Coppell, TX, United States (Remote available) - **Experience:** Experienced - **Contract:** Temporary to permanent - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Computer Vision, Microsoft Azure, Cluster Analysis, Software Debugging, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Smart Devices, Data Processing, Google Cloud, Pytorch, Transfer Learning, Model Validation, Information Technology, ONNX (Open Neural Network Exchange) Format, Performance Monitor, Machine Learning Operations, TensorRT, Software Version Control, Data Pipelines - **Published:** August 20, 2026 - **Apply:** https://www.dice.com/job-detail/5071f421-3940-4251-800b-94728dec65a3 ## About the Role * Computer Vision (Detection, Segmentation, Classification, OCR) * Python * PyTorch and/or TensorFlow * Machine Learning Model Development & Optimization * Image & Video Analysis * Taking Models from Prototype to Production, * 3-5 years of hands-on experience building computer vision and machine learning models. * Proven track record taking models from experimentation to production. Skills: * Proficiency in both modern AI-based CV models (CNNs, transformers, embeddings) and traditional computer vision * Strong Python skills for CV/ML development, data processing, and experimentation. * Experience with PyTorch or TensorFlow. * Hands-on experience with detection, segmentation, classification, and image/video analysis. * Practical knowledge of computer vision hardware-cameras, sensors, lighting, and edge devices-and the real-world constraints that affect data quality and model performance. * Experience with broader ML problems: time-series modeling, anomaly detection, clustering, and data analysis. Abilities: * Strong analytical and performance-debugging skills. * Able to evaluate model options and turn business problems into practical AI solutions. * Strong problem-solving skills and ability to work in a fast-paced, agile environment. Education: * Bachelor's or Master's degree in Computer Science, Engineering or a related field., * Experience deploying models to edge devices or optimizing for inference (quantization, pruning, TensorRT, ONNX). * Familiarity with MLOps practices: experiment tracking, model versioning, and drift/performance monitoring. * Experience with cloud platforms (Azure, AWS, or Google Cloud Platform) and GPU-based training. * Experience working with retail, IoT, or real-world imaging datasets. ## Description * Applied Model Development: Own the end-to-end development of computer vision and ML models-covering detection, segmentation, classification, OCR and image/video analysis. * Model Evaluation & Selection: Evaluate model options, benchmark trade-offs, and recommend the right approach for each business problem. * Training & Fine-Tuning: Train, fine-tune, and optimize models using PyTorch or TensorFlow, including transfer learning and data-efficient techniques. * Performance Analysis: Define metrics, analyze model performance, diagnose failure modes, and iterate to meet accuracy and latency targets. * Hardware-Aware Engineering: Account for the real-world constraints of cameras, sensors, lighting, and edge devices that affect data quality and model performance. * Data Pipelines: Build and maintain data, labeling, and evaluation pipelines that support reliable experimentation and deployment. * Collaboration: Work with software, hardware, and MLOps engineers to take models from prototype to production. ## Related Videos - [Developing an AI.SDK](https://www.wearedevelopers.com/videos/198-developing-an-ai-sdk) - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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