Position: AI & Machine Learning Intern

Company: INLIGHN TECH

Location: Remote (100% Virtual)

Duration: 3 months

Top Interns Stipend: ₹15,000

Potential for Full-Time Employment: Based on performance

Certificate of Internship Provided

About INLIGHN TECH:

INLIGHN TECH is committed to nurturing the next generation of tech professionals by offering immersive internship programs. Our AI & Machine Learning Internship is designed to give students and recent graduates valuable hands-on experience with intelligent systems, data-driven models, and innovative solutions in the AI domain.

Role Overview:

As an AI & Machine Learning Intern at INLIGHN TECH, you will work closely with our engineering and data teams to build, train, and deploy machine learning models. This internship offers a great opportunity to gain experience with real-world AI applications, enhance technical skills, and contribute to innovative projects.

Key Responsibilities:

• Assist in collecting, preprocessing, and analyzing datasets for machine learning models.
• Implement and test machine learning algorithms using Python and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Support in model evaluation, tuning, and deployment.
• Collaborate with team members to explore AI-driven solutions for real-world challenges.
• Document experiments, results, and provide regular progress updates.

Qualifications:

• Currently pursuing or recently completed a degree in Computer Science, Data Science, AI, or a related field.
• Strong foundation in Python and understanding of machine learning concepts.
• Familiarity with ML libraries and frameworks such as NumPy, pandas, scikit-learn, TensorFlow, or PyTorch.
• Analytical mindset with attention to detail and problem-solving skills.
• Ability to work independently and in a collaborative team environment.

Benefits:

• Practical experience with real AI & ML projects.
• Certificate of Internship upon successful completion.
• Letter of Recommendation to support your academic or professional pursuits.
• Opportunity to build a strong portfolio and apply theoretical knowledge in real scenarios.