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Machine Learning Intern (Remote) Skillzenloop
Location: Remote
Type: Full-Time Internship
Stipend: 17,000/month
Duration: 13 Months
Skillzenloop is hiring a Machine Learning Intern to work on real-world datasets and develop intelligent models for solving business problems. This role is ideal for students and freshers who want hands-on experience in machine learning, data modeling, and AI-driven solutions in a practical, project-based environment.
Key Responsibilities
Collect, clean, and preprocess data for machine learning tasks
Build, train, and evaluate machine learning models
Work on supervised and basic unsupervised learning techniques
Perform feature selection and model optimization
Analyze model performance and improve accuracy
Collaborate with teams to understand business problems and translate them into ML solutions
Work with Python libraries such as scikit-learn, Pandas, and NumPy
Document models, processes, and results
Required Skills
Basic knowledge of Python programming
Understanding of machine learning concepts and algorithms
Familiarity with libraries like scikit-learn, Pandas, and NumPy
Basic understanding of statistics and probability
Knowledge of data preprocessing and feature engineering
Familiarity with data visualization tools is a plus
Strong analytical and problem-solving skills
Ability to work independently in a remote environment
Eligibility Criteria
Students or recent graduates from Computer Science, Data Science, AI, or related fields
Freshers with basic machine learning knowledge are encouraged to apply
Candidates with academic or personal ML projects will have an advantage
Must be available for a full-time remote internship
Perks and Benefits
Monthly stipend of 17,000
Hands-on experience with real-world machine learning projects
Internship completion certificate
Opportunity to build a strong machine learning portfolio
Exposure to industry-relevant tools and workflows
Learning-focused and growth-oriented environment
This internship is a strong opportunity for individuals looking to start their career in machine learning and gain practical experience in building intelligent systems and predictive models.
Job ID: 145099411