Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
Coppell, TX, United States
Posted
Yesterday
AWSMLOpsMachine LearningAzureComputer VisionGoogle CloudIoTPyTorchPythonTensorFlow
Job Description
Computer Vision / AI Engineer II
Location: Coppell, TX
Duration: 6 Months Contract with Potential Extension / Conversion
Job Summary
We are looking for a Computer Vision / AI Engineer with strong hands-on experience developing and optimizing machine learning and computer vision models. The ideal candidate will work across model development, evaluation, training, and production deployment for real-world image and video applications.
Required Skills
- 3–5 years of hands-on experience developing Computer Vision / Machine Learning models.
- Strong Python programming skills.
- Experience with PyTorch and/or TensorFlow.
- Hands-on experience with object detection, segmentation, classification, and OCR.
- Strong experience with image and video analysis.
- Experience training, fine-tuning, and optimizing ML/CV models.
- Experience with modern computer vision approaches including CNNs, Transformers, and embeddings.
- Knowledge of traditional computer vision techniques.
- Proven experience taking models from prototype/experimentation through production.
- Strong experience evaluating model performance, defining metrics, analyzing failure modes, and improving accuracy/latency.
- Experience building data, labeling, and model evaluation pipelines.
- Strong analytical and problem-solving skills.
Preferred Skills
- Experience deploying models to edge devices.
- Model inference optimization using TensorRT, ONNX, quantization, or pruning.
- Experience with MLOps, including experiment tracking, model versioning, and performance monitoring.
- Experience with AWS, Azure, or Google Cloud Platform.
- GPU-based model training.
- Experience working with cameras, sensors, lighting, and other computer vision hardware.
- Experience with retail, IoT, or real-world imaging datasets.
- Strong collaboration experience with software, hardware, and MLOps teams.
Education
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
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