Senior Computer Vision Engineer

About the Role:

As a Computer Vision Engineer, you will play a key role in our AI team, designing and building solutions that make legal collaboration seamless and accessible. You will work on a cutting-edge product that leverages computer vision and other advanced AI techniques to support the automotive industry. Our platform, SelfInspection, enables automated vehicle inspections. Users capture photos of a vehicle's exterior, interior, and tires, which are then analyzed by our AI and experts to generate detailed condition reports. The first version of the product is live, and we are actively developing its second iteration.

Responsibilities:

• Train, evaluate, and deploy computer vision models for tasks such as instance segmentation, object detection, classification, and tracking
• Improve and optimize existing computer vision models
• Prepare high-quality training datasets using annotated data provided by the annotation team
• Stay current with advancements in the computer vision field to ensure the use of efficient and modern approaches
• Collaborate with C-level stakeholders to define technical requirements and specifications for new features

Qualifications:

• Minimum of 5 years of hands-on experience in machine learning, computer vision, or a closely related field
• Proven experience in training, evaluating, and optimizing deep learning models for production environments
• Strong background in data collection, preprocessing, augmentation, and annotation workflows
• Bachelor's, Master’s, or Ph.D. degree in Computer Science, Electrical Engineering, Mathematics, or a related discipline (preferred but not required)

Skills:

• Hands-on experience with deep learning frameworks, particularly PyTorch and/or TensorFlow
• Deep understanding of convolutional neural networks (CNNs), transformers, and core computer vision tasks such as image classification, object detection, segmentation, and tracking
• Proficiency with scientific and image processing libraries such as NumPy, OpenCV, and scikit-learn
• Familiarity with model deployment techniques (e.g., ONNX, TensorRT, TorchScript, TensorFlow Lite) and performance optimization strategies
• Strong problem-solving skills and the ability to decompose complex vision tasks into modular components
• Excellent communication and collaboration skills across both technical and non-technical teams

Will be a Plus:

• Interest in prototyping and experimenting with new computer vision techniques
• Experience designing AI products from the ground up, with a solid understanding of AI system architecture