Machine Learning Intern

Role Overview

At AbsoluteHub, we're doing things differently. This isn't a traditional job or a standard internship—it’s an open collaboration program designed for aspiring machine learning engineers and practitioners to gain hands-on, real-world experience. If you are self-taught, a student, or transitioning careers, this is a space for you to work on actual predictive modeling challenges, build your portfolio, and learn by doing alongside our team.

Responsibilities

• Data Engineering & Feature Extraction: Preprocess, clean, and transform messy structured and unstructured datasets to extract meaningful features for modeling.
• Train & Tune Algorithms: Build, evaluate, and optimize machine learning models across supervised and unsupervised domains (e.g., classification, regression, clustering).
• Experimentation & Hyperparameter Tuning: Perform systematic model comparisons, cross-validation, and hyperparameter optimization to improve predictive performance.
• Model Validation & Metrics Analysis: Track experiment results using key metrics (precision, recall, F1-score, ROC-AUC, RMSE) and address issues like bias, variance, and overfitting.

Requirements

• Deep interest in machine learning, statistical modeling, and data science.
• Solid grasp of Python and standard data libraries.
• Familiarity with core ML concepts, mathematical principles (linear algebra, calculus, probability), and algorithmic trade-offs.
• Curious, driven, and comfortable asking questions.

Nice to Have

• Hands-on experience with frameworks like PyTorch, TensorFlow, or XGBoost.
• Experience with SQL databases.
• Experience building an end-to-end ML pipeline.

Benefits

• Remote & Flexible work environment.
• Real Portfolio Projects including functional machine learning pipelines.
• Direct Mentorship with code reviews and statistical feedback.
• Certificate of completion and a strong letter of recommendation.

Skills

• Python
• Pandas
• Scikit-learn
• PyTorch
• SQL