Entry-Level Machine Learning Engineer

Key Responsibilities

• Develop, train, test, and evaluate machine learning models using Python.
• Collect, clean, preprocess, and analyze structured and unstructured datasets.
• Implement machine learning algorithms for classification, regression, clustering, and prediction tasks.
• Work with libraries such as NumPy, Pandas, Scikit-learn, and Matplotlib.
• Assist in developing deep learning and AI-based solutions using TensorFlow or PyTorch.
• Evaluate model performance, troubleshoot issues, and improve accuracy.
• Collaborate with data engineers and software developers to integrate ML models into applications.
• Document experiments, findings, and model development processes.

Requirements & Tech Stack

• Basic to intermediate knowledge of Python programming.
• Understanding of machine learning algorithms and fundamental statistical concepts.
• Familiarity with NumPy, Pandas, Scikit-learn, and data visualization tools.
• Knowledge of SQL and database fundamentals.
• Understanding of data preprocessing, feature engineering, model evaluation, and validation techniques.
• Basic familiarity with TensorFlow, PyTorch, or other deep learning frameworks.
• Strong analytical, problem-solving, and communication skills.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Statistics, Mathematics, or a related field.
• Academic projects, internships, or personal projects in machine learning or artificial intelligence.
• Familiarity with Git/GitHub and Jupyter Notebook.
• Basic knowledge of cloud platforms such as AWS, Azure, or Google Cloud is a plus.