Self Inspection is an AI SaaS platform in AutoTech that is redefining the $30B market for vehicle inspection by delivering end-to-end automation, massive reduction of costs and decisive increase in trust and quality to the industry. Our technology uses AI to enable anyone with a phone to complete a computer vision-based guided vehicle inspection in a few minutes, receiving a digital report with body damage estimation.

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, Self Inspection, enables automated vehicle inspections. Users capture photos of a vehicle's exterior, interior, and tires, which are then analyzed by our AI and in-house 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

Required Languages:

• English A2 - Elementary