SDE-1 (Computer Vision Engineer)
Master-Works
Posted: April 12, 2026
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Quick Summary
Design and implement robust, industry-grade algorithms for computer vision problems, working with deep learning frameworks such as OpenCV, Python, and Keras. Utilize Docker, Kubernetes, and model compression techniques for deployment. Develop state-of-the-art deep learning models for computer vision tasks.
Required Skills
Job Description
Responsibilities
• Solve real-world Computer Vision problems using cutting-edge techniques.
• Design and implement robust, industry-grade algorithms.
• Utilize OpenCV, Python, and deep learning frameworks for model training.
• Work with deep learning libraries such as Keras, TensorFlow, and PyTorch.
• Develop integrations with internal and external microservices.
• Implement deployment practices using Docker, Kubernetes, and model compression techniques.
• Research the latest technologies and develop proof of concepts (POCs).
• Build and train state-of-the-art deep learning models for:
• Object Detection (Mandatory)
• Segmentation
• Classification
• Object Tracking
• Visual Style Transfer
• Generative Adversarial Networks (GANs)
• Collaborate with researchers and engineers to develop and deploy Computer Vision solutions.
• Plan and execute Computer Vision research projects, defining scope, objectives, and deliverables.
• Provide specialized technical and scientific research support for ongoing and new AI initiatives.
Requirements:
Required Skills
• C++ (Mandatory)
• Python (Mandatory)
• Image Processing (Mandatory)
• Computer Vision (Mandatory)
• Deep Learning (Mandatory)
• Object Detection
• Machine Learning
• Pattern Recognition
• Artificial Intelligence (AI)
• Data Science
• Generative Adversarial Networks (GANs)
• Flask
• SQL