Responsibilities: Collaborate with cross-functional teams to understand business objectives and identify opportunities for applying machine learning techniques. Design, develop, and implement machine learning models and algorithms for various applications, including but not limited to natural language processing, computer vision, recommendation systems, and predictive modeling. Collect, preprocess, and analyze large datasets to derive insights and train machine learning models. Evaluate and fine-tune existing models for enhanced performance and scalability. Stay updated on the latest advancements in machine learning, artificial intelligence, and related fields to bring innovative solutions to the team. Collaborate with data engineers and software developers to integrate machine learning models into production systems. Participate in code reviews, documentation, and knowledge sharing to foster a collaborative and learning-oriented environment. Set up machine learning models on cloud platforms. Skills: Strong proficiency in programming languages such as Python, Java, or R. Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, etc. Solid understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning. Proficiency in data preprocessing, feature engineering, and model evaluation techniques. Experience in working with large datasets and proficiency in data manipulation using tools like Pandas, NumPy, etc. Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for deploying and managing machine learning models. Experience with version control systems such as Git for managing codebase and collaborating with team members. Strong problem-solving skills and ability to translate business requirements into technical solutions. Excellent communication skills and ability to collaborate effectively in a team environment.