Machine Learning Intern

Job Description

We are seeking a skilled and motivated Machine LearningEngineer to join our dynamic team. The ideal candidate will have a strongbackground in machine learning, large language models (LLMs), and naturallanguage processing (NLP). The candidate should hold a B.Tech/Master's degreeand possess some hands-on experience in the field. As a Machine LearningEngineer, you will be responsible for developing, implementing, and optimizingmachine learning models to contribute to the advancement of our technology.

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Roles & Responsibilities

• Algorithm Development: Design and implement machine learning algorithms, with a focus on applications in large language models and natural language processing.
• Large Language Models (LLMs): Work with and enhance large language models to improve natural language understanding and generation capabilities.
• Natural Language Processing (NLP): Apply NLP techniques to solve complex problems related to language understanding, sentiment analysis, and information extraction.
• Model Training and Evaluation: Train and evaluate machine learning models using relevant datasets, ensuring high performance and accuracy.
• Feature Engineering and Data Preprocessing: Conduct feature engineering and data preprocessing to enhance the robustness of models.
• Collaboration: Collaborate with cross-functional teams, including software engineers, data scientists, and domain experts, to integrate machine learning solutions into our products.
• Documentation: Maintain comprehensive documentation of models, algorithms, and experiments for reproducibility and knowledge transfer

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Qualification

• Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field (B.Tech/M.Tech).
• Some hands-on experience in machine learning, large language models, and natural language processing.
• Strong programming skills in Python and experience with relevant libraries and frameworks (e.g., TensorFlow, PyTorch, spaCy).
• Understanding of machine learning algorithms and techniques.
• Familiarity with large language models and their applications.
• Knowledge of natural language processing techniques and tools.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration skills.
• Ability to work in a fast-paced and collaborative environment.

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