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Job description for AI Engineer at Visi Global Teknologi
- Use machine learning method such as, regression, clustering, random forest, support vector machine, convolutional neural network and recurrent neural networks for the purpose of innovating and developing novel products
- Utilize established machine learning frameworks such as TensorFlow, PyTorch, MXNet, or cloud platform such as Microsoft Azure, Aws Sagemaker and others to facilitate the development of innovative machine learning models
- Establish and maintain an end-to-end pipeline for the development of machine learning models. This involves orchestrating the entire lifecycle, encompassing data collection, preprocessing, feature engineering, model training, evaluation, and deployment, ensuring a seamless and efficient workflow.
- Implement the deployment of machine learning models into a production environment.
- Establish seamless integration of the machine learning solution with the client's system.
- Develop a systematic pipeline for monitoring the performance of machine learning solutions and implementing continuous improvement measures.
- BS or higher degree in engineering (Preferred Mathematic, Statistic or Computer Science) or equivalent relevant experience
- Have a foundational comprehension of the fundamental principles underpinning machine learning methodologies, encompassing key concepts such as supervised learning, unsupervised learning, features, labels, model evaluation, overfitting, underfitting, cross-validation, bias and variance management, ensemble methods, feature engineering, hyperparameter tuning, gradient descent optimization, neural networks, loss functions, clustering, and regression.
- Possesses proficiency in the application of various machine learning frameworks, including TensorFlow, PyTorch, MXNet, and platforms such as Google Cloud AI Platform, Microsoft Azure Machine Learning, AWS Sagemaker adeptly utilizing these technologies to address intricate data-driven challenges and develop sophisticated analytical solutions.
- Able to integrate and proficient in backend frameworks such as Django, Flask, Express.
- Capable of deploying solutions on diverse platforms, including on-site servers, IoT devices, or cloud environments.
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