AI Solutions Developer

As an AI Engineer, your role involves leveraging data visualization to derive insights in the energy sector. You will be responsible for implementing data science solutions utilizing various techniques such as machine learning, NLP, Gen AI, and deep learning to optimize business outcomes. Evaluating the quality and effectiveness of data sources and collection methodologies will be a crucial part of your responsibilities. Additionally, translating complex technical concepts into clear, actionable insights is essential for this role. Key Responsibilities: - Utilize cloud platforms, specifically Azure, to design, develop, and deploy data science solutions. This includes expertise in Azure Machine Learning, Azure Databricks, and Azure Storage. - Demonstrate proficiency in Python for tasks such as data manipulation, analysis using Pandas and NumPy, as well as machine learning and deep learning using scikit-learn, TensorFlow, and PyTorch. - Develop and deploy machine learning models including supervised and unsupervised learning, regression, classification, clustering, and model evaluation and selection. - Utilize optimization techniques such as linear and nonlinear programming, stochastic optimization to enhance asset performance. - Create and deploy deep learning models like Convolutional neural networks (CNNs), Recurrent neural networks (RNNs), Long short-term memory (LSTM) networks. - Explore and apply generative AI techniques like Generative adversarial networks (GANs), Variational autoencoders (VAEs), Transformers. Qualification Required: - Bachelors degree in computer science, Data Science, Statistics, Mathematics, or a related field; masters degree preferred. - 46 years of hands-on experience in data science or a related role, demonstrating a successful track record of project delivery. In addition to the responsibilities and qualifications mentioned above, if there are any additional details about the company provided in the job description, please provide them for a comprehensive understanding. As an AI Engineer, your role involves leveraging data visualization to derive insights in the energy sector. You will be responsible for implementing data science solutions utilizing various techniques such as machine learning, NLP, Gen AI, and deep learning to optimize business outcomes. Evaluating the quality and effectiveness of data sources and collection methodologies will be a crucial part of your responsibilities. Additionally, translating complex technical concepts into clear, actionable insights is essential for this role. Key Responsibilities: - Utilize cloud platforms, specifically Azure, to design, develop, and deploy data science solutions. This includes expertise in Azure Machine Learning, Azure Databricks, and Azure Storage. - Demonstrate proficiency in Python for tasks such as data manipulation, analysis using Pandas and NumPy, as well as machine learning and deep learning using scikit-learn, TensorFlow, and PyTorch. - Develop and deploy machine learning models including supervised and unsupervised learning, regression, classification, clustering, and model evaluation and selection. - Utilize optimization techniques such as linear and nonlinear programming, stochastic optimization to enhance asset performance. - Create and deploy deep learning models like Convolutional neural networks (CNNs), Recurrent neural networks (RNNs), Long short-term memory (LSTM) networks. - Explore and apply generative AI techniques like Generative adversarial networks (GANs), Variational autoencoders (VAEs), Transformers. Qualification Required: - Bachelors degree in computer science, Data Science, Statistics, Mathematics, or a related field; masters degree preferred. - 46 years of hands-on experience in data science or a related role, demonstrating a successful track record of project delivery. In addition to the responsibilities and qualifications mentioned above, if there are any additional details about the company provided in the job description, please provide them for a comprehensive understanding.