NLP Engineer

Role Overview: As a Machine Learning Engineer, you will utilize your expertise in Natural Language Processing (NLP), Computer Vision, Data Extraction, and Data Mining. Your proficiency in Python, Regular Expressions (Regex), SQL, PyTorch, Kubernetes, Git, and CI/CD pipeline management will be crucial. Your strong research capabilities will enable you to deliver high-quality results within fast-paced environments and tight deadlines. Your analytical and problem-solving skills will play a crucial role in the success of your projects. Key Responsibilities: - Model Development: - Design, develop, and implement NLP models and data mining algorithms for various applications. - Conduct experiments to optimize model performance and ensure robustness. - Data Preparation: - Collaborate with data engineers to gather, clean, and preprocess data for model training and evaluation. - Utilize tools and libraries for efficient data handling and feature engineering. - Packaging and Deployment: - Package machine learning models into scalable and maintainable services using best practices. - Deploy models into production environments using Kubernetes and Docker. - CI/CD Pipeline: - Design and implement CI/CD pipelines for automated testing, validation, and deployment of machine learning models. - Integrate version control best practices using Git to manage code and model versions effectively.,