Machine Learning Enginee

Role Description This is a part-time, remote Machine Learning Engineer role at SG Academy. The position focuses on designing, implementing, and evaluating machine learning models to support educational products, tools, and platforms. Day-to-day responsibilities include building and optimizing algorithms, experimenting with neural network architectures, and applying pattern recognition techniques to real-world datasets. The Machine Learning Engineer will collaborate with instructors, product teams, and developers to translate learning objectives into data-driven features, improve existing models, and document solutions for reproducibility and knowledge sharing. The role also involves code reviews, performance monitoring, and staying current with emerging machine learning methods and best practices.

Qualifications

Strong foundation in Computer Science and Algorithms, with the ability to design efficient, scalable solutions. Applied knowledge of Statistics and Pattern Recognition to analyze data, evaluate model performance, and draw meaningful insights. Hands-on experience with Neural Networks and modern machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Proficiency in programming languages commonly used in machine learning (such as Python), including version control and testing practices. Ability to work independently in a remote setting, manage part-time hours effectively, and communicate clearly with cross-functional teams. Bachelor’s degree or higher in Computer Science, Data Science, Engineering, Mathematics, or a related field, or equivalent practical experience. Experience with data preprocessing, model deployment, and cloud-based ML tools (e.g., AWS, GCP, or Azure) is beneficial. Interest in education technology and improving learning experiences through data-driven innovation is a plus.