Job Overview
Job TitleMachine Learning Intern
Job TypeFull Time
Offered Salary₹156,000
LocationHybrid
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Job Description
Machine Learning Intern (Entry Level)
SkillzenLoop is looking for passionate and analytical Machine Learning Interns who are eager to work with real datasets, build intelligent models, and develop strong skills in machine learning, predictive analytics, and AI-driven problem-solving.
Roles & Responsibilities
- Assist in data collection, preprocessing, and exploratory data analysis
- Work on machine learning models for prediction and pattern recognition
- Support model training, testing, and performance evaluation
- Use Python and relevant libraries for data science and ML projects
- Generate insights, reports, and analytical findings
- Collaborate on real-world AI and machine learning assignments
- Assist in experimentation, research, and technical documentation
Eligibility Criteria
- Freshers and students are welcome
- Basic knowledge of Python programming
- Understanding of machine learning concepts and data analysis
- Familiarity with Pandas, NumPy, Scikit-learn, or similar libraries is a plus
- Strong analytical and logical thinking skills
- Curious mindset with willingness to learn
- Good communication and problem-solving abilities
Internship Details
- Mode: Virtual / Remote
- Duration: Flexible
- Stipend: ₹13,000/month
Perks & Benefits
- Hands-on experience with real machine learning projects
- Internship Certificate
- Practical exposure to AI and ML workflows
- Skill development through project-based learning
- Top performers will receive 100% placement support
How to Apply
Interested candidates can apply by clicking on the “Apply” option. Apply before 22nd May to be considered for this opportunity.
Key skills/competency
- Machine Learning
- Python
- AI
- Predictive Analytics
- Data Analysis
- Data Preprocessing
- Model Training
- Scikit-learn
- NumPy
- Pandas
How to Get Hired at Skillzenloop
- Tailor your resume: Highlight Python skills, ML concepts, and any data analysis projects.
- Showcase your projects: Include personal or academic ML projects on your resume or GitHub.
- Emphasize learning: Demonstrate your curiosity and willingness to learn AI/ML technologies.
- Apply early: Submit your application before the deadline to ensure consideration.
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