Machine Learning Intern
@ UM IT Solutions

Hybrid
₹30,000
Hybrid
Intern
Posted 6 hours ago

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XXXXXXXX XXXXXXXXX XXXXXXXX***** @webboostsolutions.com
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Job Details

About WebBoost Solutions by UM

WebBoost Solutions by UM provides students and graduates with hands-on learning and career growth opportunities in machine learning and data science.

Role Overview

As a Machine Learning Intern, you’ll work on real-world projects gaining practical experience in machine learning and data analysis.

Responsibilities

  • Design, test, and optimize machine learning models.
  • Analyze and preprocess datasets.
  • Develop algorithms and predictive models.
  • Utilize tools like TensorFlow, PyTorch, and Scikit-learn.
  • Document findings and present insights in reports.

Requirements

  • Enrolled in or graduate of a relevant program (AI, ML, Data Science, Computer Science, etc.).
  • Strong knowledge of machine learning concepts and algorithms.
  • Proficiency in Python or R is preferred.
  • Excellent analytical and teamwork skills.

Benefits

  • Paid stipend: ₹7,500 - ₹15,000 (Performance-Based).
  • Practical machine learning experience.
  • Internship Certificate & Letter of Recommendation.
  • Opportunity to build a portfolio with real-world projects.

How to Apply

Submit your application by 12th October 2025 with the subject: "Machine Learning Intern Application".

Equal Opportunity

WebBoost Solutions by UM welcomes candidates from all backgrounds.

Key skills/competency

  • Machine Learning
  • Data Science
  • Python
  • R
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • Data Analysis
  • Algorithms
  • Teamwork
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How to Get Hired at UM IT Solutions

🎯 Tips for Getting Hired

  • Research WebBoost Solutions by UM: Understand their projects and culture.
  • Customize Your Resume: Highlight relevant ML and data skills.
  • Prepare Examples: Showcase project work and teamwork experience.
  • Practice Interviews: Cover technical and behavioral questions.

📝 Interview Preparation Advice

Technical Preparation

Review ML algorithms.
Practice Python and R coding.
Experiment with TensorFlow exercises.
Study data preprocessing techniques.

Behavioral Questions

Describe your teamwork experience.
Explain problem-solving examples.
Discuss conflict resolution.
Share examples of handling feedback.

Frequently Asked Questions