AI Engineer

April 24

EPIC iO Technologies

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A safer, smarter & more connected world.

201 - 500

💰 $30M Debt Financing on 2022-02

Description

• Evaluate and improve the existing data infrastructure and architecture for diverse use cases, including examination of the current EPIC system for identifying areas of enhancement. • Engage in research and innovation, exploring state-of-the-art techniques and methodologies to ensure the developed applications remain at the forefront of technological advancement. • Curate and prepare datasets required for training and evaluating machine learning and deep learning models, involving data acquisition, cleansing, and organization to ensure suitability for model training and evaluation. • Utilize machine learning and deep learning techniques to train and evaluate models tailored for image and video processing tasks. • Optimize machine learning and deep learning models to enhance performance metrics such as precision and throughput, encompassing parameter adjustments, exploration of alternative architectures, and implementation of optimization techniques for superior results. • Implement computer vision algorithms for preprocessing data, ensuring proper transformation and standardization of input data before feeding into the models. • Implement strategies to ensure system scalability and adaptability to variable workloads and environments. • Productize machine learning and deep learning models by developing APIs or Python modules for seamless integration into existing platforms

Requirements

• Training Detection/Classification/Segmentation Models with PyTorch/TensorFlow: Experience in training deep learning models for detection, classification, and segmentation tasks using libraries such as PyTorch and TensorFlow. • Model Optimization with OpenVINO: Experience in optimizing deep learning models using the Intel OpenVINO tool. • Use of Docker, Nvidia-Docker, and Containers for Computer Vision/Deep Learning: Experience in using Docker containers and Nvidia-Docker for creating reproducible and portable development environments for computer vision and deep learning applications. • Proficiency in Mathematics, Probability, Statistics, and Algorithms: Strong understanding of fundamental mathematical concepts, probability, statistics, and algorithms, essential for the development and optimization of machine learning models. • Programming Language: Python: Proficiency in the Python programming language, utilized in the development of machine learning and computer vision applications. • Python Libraries: OpenCV, NumPy, Scikit-learn: Experience in using popular Python libraries for computer vision and machine learning, including OpenCV, NumPy, and Scikit-learn.

Benefits

• Bring your skills and knowledge to an innovative and growing workplace • Work and collaborate with a team who has become one of the best in the industry • Use industry-leading technology and the best tools available to ensure success • Work in a stable industry with strong growth potential • Annual day of service