Machine Learning Intern

Innovexis is excited to announce an opening for a Machine Learning Intern to join our team . This Remote internship offers a unique opportunity for aspiring machine learning professionals to gain hands-on experience in the Education Management industry, working on real-world AI and ML solutions that drive innovation in learning and talent development.
As a Machine Learning Intern, you will be involved in building, training, and evaluating machine learning models to solve practical problems. You will collaborate closely with experienced data scientists, engineers, and educators to analyze data, develop predictive models, and generate insights that support strategic and operational decision-making. This internship is ideal for candidates looking to strengthen their ML fundamentals while contributing to impactful projects in the education sector.
We offer a competitive stipend ranging from ?20,000 to ?25,000 per month, along with structured mentorship, hands-on project exposure, and opportunities for professional growth throughout the internship.
Responsibilities

• Assist in collecting, cleaning, and preprocessing datasets for machine learning tasks
  
• Develop, train, and evaluate machine learning models
• Implement algorithms for classification, regression, and prediction problems
• Analyze model performance and optimize results
• Work with large datasets to extract meaningful insights
• Collaborate with cross-functional teams to understand project requirements
• Document models, experiments, and findings clearly
• Participate in team discussions, code reviews, and brainstorming sessions
• Support deployment and testing of ML models where applicable
  

Requirements

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• Pursuing a degree in Machine Learning, Data Science, Computer Science, AI, or a related field
• Strong understanding of machine learning concepts and algorithms
• Proficiency in Python
• Familiarity with ML libraries such as Scikit-learn, TensorFlow, or PyTorch
• Basic knowledge of data preprocessing, feature engineering, and model evaluation
• Ability to explain technical concepts clearly
• Strong analytical and problem-solving skills
• Detail-oriented with a focus on accuracy and performance
• Ability to work collaboratively in a fast-paced team environment