Computer Vision Engineer at Red Alpha Cybersecurity – Central Region | Jobyssey

Position Overview

We are looking for a Computer Vision Engineer with a strong technical background in computer vision, machine learning, and software development. The candidate will develop and integrate computer vision solutions into practical, usable software systems.

Key Responsibilities

Develop, train, evaluate, and optimize computer vision and deep learning models for image and video analysis.
Build end-to-end computer vision pipelines, including data preparation, inference, post-processing, and visualization.
Develop software applications, backend services, APIs, or interfaces to integrate AI models into usable systems.
Work with image datasets, including annotation, augmentation, preprocessing, and evaluation.
Optimize model and system performance for deployment.
Collaborate with researchers, engineers, and stakeholders to translate application requirements into practical technical solutions.

Requirements

Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, Data Science, or a related discipline.
Strong background in Computer Vision and/or Deep Learning.
Strong programming skills in Python.
Experience with PyTorch or TensorFlow and computer vision libraries such as OpenCV
Experience with common computer vision tasks, including classification, object detection, segmentation, anomaly/defect detection, feature extraction, and image processing.
Strong software engineering and problem-solving skills.
Experience in developing complete applications or platforms, rather than only individual machine learning models.
Ability to work independently and translate research ideas into practical implementations.

Preferred Qualifications

Master’s degree is preferred.
Experience deploying AI/computer vision models into production or operational environments.
Knowledge of REST APIs, databases, Docker, Git, Linux, and GPU computing, and experience with web app development frameworks, such as FastAPI/Flask, Streamlit, React, or similar tools.
Experience with Vision-Language Models (VLMs), foundation models, or generative AI.
Experience in industrial computer vision, visual inspection, manufacturing, or automation.

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