Applied Computer Vision Engineer - Production-Ready ML

Hub; United States; Remoto; USD 110.000 - 170.000; Tempo pieno

Descrizione del lavoro

Hub is seeking a Computer Vision Engineer to advance our image-analysis models on an existing production platform. You will train, evaluate, and optimize deep learning models for real-world waste imagery, going beyond research to deliver robust production solutions.

You will work with datasets, apply augmentation, and iterate on architectures to improve accuracy, speed, and reliability in real-world settings. Strong Python, PyTorch or TensorFlow, and CV knowledge are essential.

Competenze

• 3+ years of hands-on computer vision and model development.
• Experience building, training, evaluating, and optimizing DL models for images.
• Solid understanding of CV architectures (e.g. CNNs, Vision Transformers).
• Strong Python
• Practical use of PyTorch or TensorFlow.
• Real-world image datasets: preprocessing, augmentation, evaluation.
• Ability to adapt and extend existing models to meet technical requirements.

Mansioni

• Develop, train, and optimize deep learning models for image analysis.
• Evaluate and extend existing model architectures.
• Improve accuracy, performance, and robustness.
• Work with image datasets: processing, augmentation, evaluation.
• Experiment with architectures and training approaches.
• Solve hard technical problems and iterate on production CV systems.

Conoscenze

Computer vision

Python

PyTorch

TensorFlow

CNNs

Vision Transformers

Data augmentation

Strumenti

OpenCV

Descrizione del lavoro

Hub is seeking a Computer Vision Engineer to advance our image-analysis models on an existing production platform. You will train, evaluate, and optimize deep learning models for real-world waste imagery, going beyond research to deliver robust production solutions.

You will work with datasets, apply augmentation, and iterate on architectures to improve accuracy, speed, and reliability in real-world settings. Strong Python, PyTorch or TensorFlow, and CV knowledge are essential.