AI Engineer Intern

0 - 3 years

0 Lacs

Posted:1 day ago| Platform: Shine logo

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Work Mode

On-site

Job Type

Full Time

Job Description

As an AI Engineer Intern at our company, you will have the exciting opportunity to work alongside experienced engineers and researchers to develop, train, and deploy AI models. Your role will involve designing, developing, and testing machine learning models, collecting, cleaning, and preprocessing datasets, and performing exploratory data analysis to extract meaningful insights. You will also collaborate with cross-functional teams to integrate models into production environments and explore emerging AI tools and platforms to enhance internal operations. Key Responsibilities: - Assist in designing, developing, and testing machine learning models. - Collect, clean, and preprocess datasets for training and evaluation. - Perform exploratory data analysis (EDA) to extract meaningful insights. - Implement and optimize algorithms using frameworks such as TensorFlow, PyTorch, or scikit-learn. - Collaborate with cross-functional teams to integrate models into production environments. - Prototype and implement AI-driven solutions to streamline internal processes. - Document findings, models, and codebase to ensure reproducibility. - Stay updated with the latest trends and advancements in AI/ML. Qualifications: - Currently pursuing a degree in Computer Science, Data Science, Engineering, Mathematics, or a related field. - Solid understanding of machine learning concepts and algorithms. - Proficiency in Python and common ML libraries (e.g., NumPy, pandas, scikit-learn). - Experience with deep learning frameworks such as PyTorch or TensorFlow is a plus. - Familiarity with NLP, computer vision, or time series analysis is a bonus. - Strong analytical and problem-solving skills. - Excellent communication and teamwork abilities. Preferred Qualifications: - Previous project or internship experience in AI/ML. - Interest or experience in productivity tools, automation, or process optimization. - Knowledge of cloud platforms (AWS, GCP, or Azure). - Experience with version control (e.g., Git) and collaborative development.,

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