Machine Learning Intern
@ UM IT Solutions

Hybrid
₹15,000
Hybrid
Intern
Posted 6 hours ago

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XXXXXXXX XXXXXXXXXXX XXXXXX***** @webboostsolutionsbyum.com
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Job Details

About the Role

The Machine Learning Intern role at WebBoost Solutions by UM offers hands-on learning and career growth opportunities in machine learning and data science. This is a paid internship offering real-world projects and a practical environment to design, test, and optimize machine learning models.

Responsibilities

  • Design, test, and optimize machine learning models.
  • Analyze and preprocess datasets.
  • Develop algorithms and predictive models for various applications.
  • Utilize tools such as TensorFlow, PyTorch, and Scikit-learn.
  • Document findings and prepare reports.

Requirements

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

Benefits

  • Performance-based stipend between ₹7,500 - ₹15,000.
  • Practical machine learning experience.
  • Internship Certificate and Letter of Recommendation.
  • Opportunity to build your portfolio with real-world projects.

How to Apply

Submit your application by 13th October 2025 using 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 Science
  • Python
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • Data Analysis
  • Model Optimization
  • Algorithm Development
  • 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 machine learning and data science skills.
  • Showcase your projects: Include real-world examples on GitHub.
  • Practice technical interviews: Prepare for algorithm and coding questions.

📝 Interview Preparation Advice

Technical Preparation

Review ML algorithms and statistical models.
Practice coding in Python and R.
Study TensorFlow, PyTorch, Scikit-learn basics.
Work on data preprocessing exercises.

Behavioral Questions

Describe a team conflict resolution experience.
Explain your time management strategies.
Discuss handling a challenging project situation.
Share an example of rapid learning adaptation.

Frequently Asked Questions