Machine Learning Intern
@ UM IT Solutions

Hybrid
₹15,000
Hybrid
Intern
Posted 7 hours ago

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XXXXXXXX XXXXXXXXXXX XXXXXXXXXX***** @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 for various applications.
  • Use tools like TensorFlow, PyTorch, and Scikit-learn.
  • Document findings and create reports to present insights.

Requirements

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

Benefits

  • Stipend: ₹7,500 - ₹15,000 (Performance-Based)
  • Practical machine learning experience.
  • Internship Certificate & Letter of Recommendation.
  • Build your portfolio with real-world projects.

How to Apply

Submit your application by 14th October 2025 with the subject: "Machine Learning Intern Application".

Equal Opportunity

WebBoost Solutions by UM is an equal opportunity employer, welcoming candidates from all backgrounds.

Key skills/competency

  • Machine Learning
  • Data Analysis
  • Python
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • Data Preprocessing
  • Algorithm Development
  • Teamwork
  • Reporting
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How to Get Hired at UM IT Solutions

🎯 Tips for Getting Hired

  • Research WebBoost Solutions by UM: Understand their mission and recent projects.
  • Customize your resume: Highlight relevant machine learning skills.
  • Prepare project examples: Showcase hands-on experience in ML.
  • Practice technical questions: Review Python and ML algorithms.

📝 Interview Preparation Advice

Technical Preparation

Review Python programming basics.
Study TensorFlow tutorials.
Practice ML model design.
Analyze sample datasets.

Behavioral Questions

Describe teamwork in previous projects.
Explain problem-solving under pressure.
Share learning from project challenges.
Discuss communication in collaborative settings.

Frequently Asked Questions