Machine Learning Intern

Machine Learning Intern

Company: SkillzenLoop

Location: Remote

Employment Type: Internship (Full-time)

Duration: 1–3 Months

Stipend: ₹15,000 per month

Role Description

SkillzenLoop is looking for a data-driven and curious Machine Learning Intern to join our AI/ML team. In this role, you will assist in developing and deploying predictive models that help solve real-world business challenges. You will gain hands-on experience in the entire ML lifecycle, from data preprocessing and feature engineering to model evaluation and optimization.

Primary Responsibilities

• Data Preparation: Clean, preprocess, and perform Exploratory Data Analysis (EDA) on structured and unstructured datasets.

• Model Development: Assist in building and training machine learning models using libraries like Scikit-learn, TensorFlow, or PyTorch.

• Feature Engineering: Identify and create relevant features to improve model performance and accuracy.

• Evaluation: Test and validate models using appropriate metrics (Accuracy, F1-score, RMSE, etc.) and perform hyperparameter tuning.

• Research: Stay updated on the latest AI/ML trends and assist in implementing state-of-the-art algorithms for internal projects.

Requirements

• Education: Currently pursuing or a recent graduate in Computer Science, Data Science, Artificial Intelligence, Statistics, or a related field.

• Programming Skills: Strong proficiency in Python and libraries such as Pandas, NumPy, and Matplotlib.

• ML Fundamentals: Solid understanding of supervised and unsupervised learning algorithms (Linear Regression, Random Forest, Clustering, etc.).

• Mathematics: Good grasp of Linear Algebra, Calculus, and Probability/Statistics.

• Tools: Familiarity with Jupyter Notebooks and Git for version control.

Internship Benefits

• Stipend: A monthly payment of ₹15,000.

• Certification: Official Internship Completion Certificate from SkillzenLoop.

• Professional Growth: Performance-based Letter of Recommendation (LoR).

• Mentorship: Hands-on guidance from experienced Data Scientists and ML Engineers.

• Work Style: 100% remote work with a focus on research, experimentation, and results.

Company: SkillzenLoop

Location: Remote

Employment Type: Internship (Full-time)

Duration: 1–3 Months

Stipend: ₹15,000 per month

Role Description

SkillzenLoop is looking for a data-driven and curious Machine Learning Intern to join our AI/ML team. In this role, you will assist in developing and deploying predictive models that help solve real-world business challenges. You will gain hands-on experience in the entire ML lifecycle, from data preprocessing and feature engineering to model evaluation and optimization.

Primary Responsibilities

• Data Preparation: Clean, preprocess, and perform Exploratory Data Analysis (EDA) on structured and unstructured datasets.

• Model Development: Assist in building and training machine learning models using libraries like Scikit-learn, TensorFlow, or PyTorch.

• Feature Engineering: Identify and create relevant features to improve model performance and accuracy.

• Evaluation: Test and validate models using appropriate metrics (Accuracy, F1-score, RMSE, etc.) and perform hyperparameter tuning.

• Research: Stay updated on the latest AI/ML trends and assist in implementing state-of-the-art algorithms for internal projects.

Requirements

• Education: Currently pursuing or a recent graduate in Computer Science, Data Science, Artificial Intelligence, Statistics, or a related field.

• Programming Skills: Strong proficiency in Python and libraries such as Pandas, NumPy, and Matplotlib.

• ML Fundamentals: Solid understanding of supervised and unsupervised learning algorithms (Linear Regression, Random Forest, Clustering, etc.).

• Mathematics: Good grasp of Linear Algebra, Calculus, and Probability/Statistics.

• Tools: Familiarity with Jupyter Notebooks and Git for version control.

Internship Benefits

• Stipend: A monthly payment of ₹15,000.

• Certification: Official Internship Completion Certificate from SkillzenLoop.

• Professional Growth: Performance-based Letter of Recommendation (LoR).

• Mentorship: Hands-on guidance from experienced Data Scientists and ML Engineers.

• Work Style: 100% remote work with a focus on research, experimentation, and results.