Machine Learning Intern – Python & TensorFlow (Remote)

Build your skills in real-world AI projects with a paid, remote-friendly Machine Learning Internship.  

Key Responsibilities  

- Clean, label, and validate raw data from finance, healthcare, and media domains.  

- Code baseline models in Python using scikit-learn and TensorFlow.  

- Debug minor issues, run A/B tests, and track experiment metrics.  

- Maintain and version datasets in Git and DVC to ensure reproducibility.  

- Document pipelines, findings, and model decisions for senior review.  

- Research recent ML papers, summarize insights, and propose small POCs.  

- Collaborate with data engineers, product managers, and UX designers during agile sprints.  

Required Qualifications  

- Bachelor’s degree in Computer Science, Data Science, or a related STEM field.  

- Solid Python fundamentals plus NumPy, pandas, and Jupyter notebooks.  

- Introductory knowledge of supervised and unsupervised learning algorithms.  

- Familiarity with scikit-learn model APIs and TensorFlow or PyTorch basics.  

- Comfort with Linux command line, Git branching, and pull requests.  

- Analytical mindset, strong verbal and written communication, eagerness to learn.  

Preferred Skills (Nice to Have)  

- Coursework or projects in deep learning, NLP, or computer vision.  

- Exposure to AWS or Google Cloud ML services.  

- SQL proficiency and basic ETL concepts.  

- Experience with experiment tracking tools such as MLflow or Weights & Biases.