AI Research Assistant — Machine Learning & AI

AI Research Assistant — Machine Learning & AI

About Studyfetch

Study Fetch is the #1 AI-native learning platform globally, transforming how millions of students learn through personalized AI-powered education. We’re growing fast with backing from top-tier investors and a mission that’s redefining the future of education and ethical learning.

We are looking for a highly motivated Master's student in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field to join our AI research team on a part-time basis.

Our research focuses primarily on the intersection of artificial intelligence and education, including the development and evaluation of AI systems that can improve teaching and learning. You will work directly with researchers and engineers on projects involving machine learning, generative AI, large language models, multimodal AI, educational data, model evaluation, and AI systems.

This is a hands-on research position. You will not simply be assisting with administrative research tasks—you will be expected to read papers, implement ideas, run experiments, analyze results, and contribute to the development of new research directions.

Depending on your interests and experience, your work may include developing and evaluating models, building research datasets, designing benchmarks and evaluation methodologies, reproducing published research, fine-tuning open-source models, analyzing educational data, and investigating novel applications of AI in education.

You will also contribute to the broader research development process, including identifying relevant research opportunities, analyzing RFPs and funding opportunities, and assisting with grant and research proposal development.

• Read and analyze recent research papers in machine learning, AI, and AI in education.
• Implement and reproduce methods from recent research.
• Design and conduct controlled experiments and ablation studies.
• Train, fine-tune, and evaluate machine learning models.
• Develop datasets and data-processing pipelines for AI research.
• Build and maintain evaluation and benchmarking systems.
• Analyze model performance and experimental results.
• Investigate new approaches to improving AI capabilities, reliability, and effectiveness in educational settings.
• Develop research prototypes in Python and modern ML frameworks.
• Analyze educational datasets and student interaction data to identify research opportunities and patterns.
• Document experiments, findings, and methodologies.
• Collaborate with researchers and engineers to refine research hypotheses.
• Contribute to technical reports, research papers, presentations, and potentially open-source projects.
• Research and analyze RFPs, grant opportunities, and government or foundation funding programs relevant to AI and education.
• Assist with the development of grant proposals, research proposals, technical narratives, and supporting materials.
• Help identify research questions and proposed technical approaches that align with funding opportunities.
• Track relevant developments in AI research, education technology, and government research priorities.

Our research primarily focuses on the application and development of AI for education. Projects may span several areas, including:

• Generative AI
• Natural language processing
• AI tutoring and educational agents
• Personalized learning
• Student modeling and learning analytics
• Model training and fine-tuning
• Reinforcement learning and post-training
• AI evaluation and benchmarking
• Representation learning
• Retrieval-augmented generation (RAG)
• Educational datasets and data infrastructure
• AI safety, reliability, and evaluation in education

You do not need experience in all of these areas. Depth in one area, strong research fundamentals, and demonstrated ability to learn quickly are more important than breadth.

• Currently pursuing or recently completed a Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, Statistics, Electrical Engineering, or a closely related field.
• Strong foundation in machine learning and deep learning.
• Experience…