AI & ML Internship
2 weeks ago
AI/ML Internship Job Description (4-Month Training)
Position: AI/ML Intern
Duration: 4 Months (Full-time)
Type: Internship with Training Certificate & Project Portfolio
Start Date: Immediate (Flexible for Students)
Position Overview
Assist in developing machine learning models, data preprocessing, and AI research projects for real-world applications. Gain hands-on experience with Python, TensorFlow/PyTorch, and deployment workflows while contributing to production-ready AI solutions. Ideal for final-year students or fresh graduates building AI/ML portfolios.
Key Responsibilities
- Perform data cleaning, feature engineering, and preprocessing using Pandas/Numpy for ML tasks.
- Train, tune, and evaluate models with Scikit-learn, TensorFlow/Keras, or PyTorch on supervised/unsupervised datasets.
- Assist in AI model deployment strategies, including Flask/Docker basics and cloud workflows (AWS/Azure intro).
- Conduct research on AI trends, analyze datasets, and document experiments/findings.
- Collaborate with engineering teams on model testing, optimization, and technical reports.
- Build 2-3 portfolio projects (e.g., predictive models, NLP tasks) with mentor guidance.
Required Skills & QualificationsCategoryRequirementsProgrammingPython proficiency; familiarity with Pandas, NumPy, Scikit-learn ML KnowledgeUnderstanding of algorithms (regression, classification, clustering); basic deep learning Math/StatsLinear algebra, calculus, probability; SQL basics ToolsTensorFlow/PyTorch (beginner level), Git; bonus: cloud platforms Soft SkillsProblem-solving, communication, teamwork; curiosity for AI research EducationPursuing B.Tech/M.Tech CS/Data Science/AI (3rd/4th year preferred)
No prior professional experience required; personal projects or coursework suffice.
Internship Structure & Training
Weekly Breakdown (16 Weeks Total):
- Weeks 1-4: Data handling, ML fundamentals, 1st project (e.g., classification model).
- Weeks 5-8: Deep learning, model optimization, 2nd project (e.g., computer vision).
- Weeks 9-12: Deployment, research, advanced topics (NLP/RL intro).
- Weeks 13-16: Capstone project, presentation, portfolio review.
Benefits:
- Mentorship from industry experts.
- Completion certificate & LinkedIn recommendation.
- Access to datasets, GPU resources, and code repositories.
- Networking with AI professionals.
Application Process
Submit resume, GitHub/portfolio, and 1-page cover letter. Shortlisted candidates complete a 1-hour Python/ML coding test. Interviews focus on problem-solving over experience.
Job Type: Full-time
Pay: ₹273, ₹1,433,495.37 per year
Work Location: In person
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