Role Overview

We are seeking a talented and motivated Computer Vision Engineer to design, develop, and deploy vision-based AI systems. You will work closely with a dynamic team of engineers and researchers to tackle challenges in image processing, object detection, and pattern recognition, delivering state-of-the-art solutions to industry problems.

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Key Responsibilities

• Design and implement computer vision algorithms for tasks such as object detection, segmentation, and classification.

• Build and optimize deep learning models for real-time and large-scale applications.

• Develop and maintain robust pipelines for data preprocessing, training, and evaluation.

• Integrate computer vision systems with existing infrastructure or customer platforms.

• Collaborate with cross-functional teams to define project requirements and deliver solutions.

• Stay updated with the latest advancements in computer vision and AI technologies.

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Required Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related fields.

• 3+ years of experience in computer vision and deep learning.

• Strong programming skills in Python, with experience in libraries such as OpenCV, TensorFlow, and PyTorch.

• Hands-on experience with vision-based neural network architectures (e.g., CNNs, GANs, Vision Transformers).

• Proficiency in image and video processing techniques.

• Experience with deploying models in production environments, including optimization and inference.

• Familiarity with cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes).

• Excellent problem-solving and debugging skills.

• Strong communication and teamwork abilities.

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Preferred Qualifications

• Experience with 3D vision, SLAM, or multi-camera systems.

• Knowledge of hardware and software integration for edge devices.

• Background in robotics or autonomous systems.

• Experience with dataset creation and annotation tools.

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What We Offer

• Competitive salary and performance-based bonuses.

• Opportunities for professional growth and learning.

• A collaborative and inclusive work culture.

• Access to cutting-edge tools and resources.

• End to End Product Development Experience.