Job Title: Computer Vision Engineer

Job Description

We are seeking a Computer Vision Engineer who is skilled in models and feature extraction methods for high-performance object detection and scene understanding. The candidate should also be knowledgeable in classical machine learning principles. This role requires a Bachelor's degree in Computer Science, Electrical Engineering, Robotics, Mathematics, or a related field.

Responsibilities

• Develop and optimize computer vision algorithms and solutions to enable autonomous vehicles to interpret and understand visual data.
• Work on projects including image recognition, object detection, video analysis, and deep learning applications.
• Design, develop, and implement computer vision algorithms for applications such as image classification, object detection, and segmentation.
• Train and fine-tune deep learning models for visual data analysis, ensuring high accuracy and performance.
• Perform data preprocessing, augmentation, and develop annotation tools for large-scale image and video datasets.
• Develop and optimize computer vision pipelines for real-time and scalable performance in production environments.
• Implement and test solutions on various hardware platforms, such as GPUs, embedded systems, and edge devices.
• Collaborate with cross-functional teams to integrate vision systems into products.
• Conduct experiments and evaluations to measure the performance and efficiency of vision algorithms.
• Stay up to date with the latest research, trends, and advancements in computer vision and machine learning.
• Troubleshoot and resolve issues related to model accuracy, performance, and system integration.
• Provide technical documentation and support for computer vision solutions and algorithms.
• Ensure the deployment of robust and maintainable vision-based systems in real-world applications.
• Optimize algorithms for computational efficiency, including memory and processing time constraints.

Essential Skills

• Strong foundation in computer vision techniques, machine learning, and programming.
• Experience in deploying real-world applications.
• Proficiency in deep learning models and feature extraction methods like SIFT and HOG.
• Knowledge of classical machine learning principles, including linear and logistic regression, SVMs, decision trees, k-Nearest Neighbors, and probabilistic classifiers.
• Expertise in Python and C++ for computer vision algorithms.
• Experience with CNNs and RNNs for visual data analysis.
• Ability to implement solutions on various hardware platforms.

Additional Skills & Qualifications

• Knowledge of YOLO and unmanned systems.
• Experience with real-time operating systems.
• Ability to collaborate with cross-functional teams.
• Experience in research and development.

Work Environment

The work environment includes office settings, research and development, and manufacturing facilities. The role requires presence at the assigned worksite during designated hours, with exceptions for PTO and specific leaves. The candidate will work with various technologies and equipment, including GPUs, embedded systems, and edge devices.