AI and Machine Learning Intern – Data Modeling

Job Description

Job Summary

AIWorks Labs is seeking a passionate and motivated AI & Machine Learning Intern to join our dynamic team, focusing on Data Modeling and predictive analytics. This internship offers an excellent opportunity to gain hands-on experience in real-world machine learning projects, exploring the full lifecycle of AI models—from data preprocessing and feature engineering to model training, evaluation, and deployment. You will work closely with our senior data scientists and AI engineers, contributing to innovative solutions that impact cutting-edge AI applications.

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Key Responsibilities

• Assist in collecting, cleaning, and preprocessing large datasets for AI model training.


• Develop and implement machine learning models for predictive and analytical tasks.


• Perform exploratory data analysis (EDA) to identify patterns, trends, and insights.


• Conduct feature engineering, selection, and dimensionality reduction to optimize model performance.


• Evaluate model performance using metrics such as accuracy, precision, recall, F1-score, and ROC-AUC.


• Collaborate with the AI team to integrate models into production systems.


• Document work, methodologies, and results in a clear and reproducible manner.


• Stay updated with the latest advancements in AI and machine learning techniques.

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Required Skills and Qualifications

• Currently pursuing or recently graduated in Computer Science, Data Science, Artificial Intelligence, Statistics, or related fields.


• Strong knowledge of Python, R, or similar programming languages.


• Familiarity with machine learning libraries such as scikit-learn, TensorFlow, PyTorch, or Keras.


• Understanding of data preprocessing, feature engineering, and model evaluation techniques.


• Ability to work with structured and unstructured data effectively.


• Basic understanding of SQL and database management.


• Strong analytical, problem-solving, and critical-thinking skills.


• Good communication skills to explain technical concepts clearly.

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Experience

• Prior internship or project experience in AI, machine learning, or data analytics is a plus.


• Experience with real-world datasets and machine learning competitions (Kaggle, Hackathons) is highly desirable.

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Working Hours

• Full-time or part-time flexible schedule, remote or on-site depending on candidate location.


• Expected commitment: 20–40 hours per week.


• Duration: 3–6 months internship, with potential for extension or full-time conversion.

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Knowledge, Skills, and Abilities

• Strong grasp of mathematical and statistical concepts for model building.


• Ability to work independently and in a team-oriented environment.


• Strong time management and multitasking abilities.


• Eagerness to learn and adapt to new AI technologies and frameworks.


• Attention to detail and a commitment to high-quality work.

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Benefits

• Hands-on experience with real-world AI projects and industry-grade datasets.


• Mentorship from experienced AI and machine learning professionals.


• Certificate of internship completion.


• Opportunity to work on projects with potential publication or product integration.


• Flexible work environment with exposure to cutting-edge AI technologies.


• Networking opportunities with experts in AI and data science fields.

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Why Join AIWorks Labs

At AIWorks Labs, we are committed to building the future of AI-driven solutions. As an intern, you will gain practical experience in machine learning and data modeling, contribute to meaningful projects, and receive guidance from an experienced team. You’ll have the chance to develop your technical expertise, analytical thinking, and problem-solving skills while being part of a forward-thinking, innovative, and inclusive workplace.

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How to Apply

Interested candidates are invited to submit their resume, a cover letter, and any relevant project portfolio or GitHub link to us with the subject line: “Application – AI & Machine Learning Intern – Data Modeling.” Applications are reviewed on a rolling basis, so early submission is encouraged.

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Job Details