Python Data Science

As an AI/ML Engineer, you will be responsible for developing, training, and deploying machine learning models using Python and various ML libraries such as scikit-learn, TensorFlow, and PyTorch. You will work on a variety of supervised and unsupervised learning models, including regression, classification, clustering, and neural networks. Additionally, you will be involved in building scalable data solutions and ML pipelines using tools like Databricks and other modern data engineering tools. Your role will also entail designing and implementing AI/ML algorithms to address complex business problems. In this role, you will have the opportunity to work with Large Language Models (LLMs) and Generative AI technologies to develop intelligent applications. You will apply prompt engineering techniques to optimize LLM-based solutions and collaborate closely with cross-functional teams, including data engineers, product teams, and business stakeholders. **Key Responsibilities:** - Develop, train, and deploy machine learning models using Python and ML libraries such as scikit-learn, TensorFlow, and PyTorch. - Work on supervised and unsupervised learning models, including regression, classification, clustering, and neural networks. - Build scalable data solutions and ML pipelines using Databricks and modern data engineering tools. - Design and implement AI/ML algorithms to solve complex business problems. - Work with Large Language Models (LLMs) and Generative AI technologies to develop intelligent applications. - Apply prompt engineering techniques to optimize LLM-based solutions. - Rapidly prototype AI solutions and experiment with new ML/AI frameworks. - Collaborate with cross-functional teams including data engineers, product teams, and business stakeholders. **Required Skills:** - Strong programming experience in Python. - Hands-on experience with scikit-learn, TensorFlow, and PyTorch. - Strong understanding of AI/ML fundamentals including supervised learning, unsupervised learning, regression models, and neural networks. - Experience working with Databricks and large-scale data platforms. - Exposure to LLMs, Generative AI, and prompt engineering. - Ability to rapidly prototype AI/ML solutions and experiment with new technologies. As an AI/ML Engineer, you will be responsible for developing, training, and deploying machine learning models using Python and various ML libraries such as scikit-learn, TensorFlow, and PyTorch. You will work on a variety of supervised and unsupervised learning models, including regression, classification, clustering, and neural networks. Additionally, you will be involved in building scalable data solutions and ML pipelines using tools like Databricks and other modern data engineering tools. Your role will also entail designing and implementing AI/ML algorithms to address complex business problems. In this role, you will have the opportunity to work with Large Language Models (LLMs) and Generative AI technologies to develop intelligent applications. You will apply prompt engineering techniques to optimize LLM-based solutions and collaborate closely with cross-functional teams, including data engineers, product teams, and business stakeholders. **Key Responsibilities:** - Develop, train, and deploy machine learning models using Python and ML libraries such as scikit-learn, TensorFlow, and PyTorch. - Work on supervised and unsupervised learning models, including regression, classification, clustering, and neural networks. - Build scalable data solutions and ML pipelines using Databricks and modern data engineering tools. - Design and implement AI/ML algorithms to solve complex business problems. - Work with Large Language Models (LLMs) and Generative AI technologies to develop intelligent applications. - Apply prompt engineering techniques to optimize LLM-based solutions. - Rapidly prototype AI solutions and experiment with new ML/AI frameworks. - Collaborate with cross-functional teams including data engineers, product teams, and business stakeholders. **Required Skills:** - Strong programming experience in Python. - Hands-on experience with scikit-learn, TensorFlow, and PyTorch. - Strong understanding of AI/ML fundamentals including supervised learning, unsupervised learning, regression models, and neural networks. - Experience working with Databricks and large-scale data platforms. - Exposure to LLMs, Generative AI, and prompt engineering. - Ability to rapidly prototype AI/ML solutions and experiment with new technologies.