Intern – Computer Vision & Machine Learning Research

Join our applied research team for a summer internship focused on advancing state-of-the-art computer vision and machine learning systems. You will work on challenging real-world problems including advanced document intelligence, synthetic document detection, and anomaly detection in complex visual data.

This role goes beyond academic experimentation — you will design, implement, and evaluate production-relevant models that directly impact high-stakes decision systems. The work spans deep learning architectures such as CNNs, Vision Transformers, multimodal models, and large language models (LLMs) applied to structured and unstructured document data.

You will collaborate closely with senior data scientists and engineers to prototype novel approaches, run rigorous experiments, and translate research ideas into scalable solutions.

What You’ll Work On

• Designing and evaluating deep learning models for document understanding and synthetic artifact detection
• Applying CNNs, Transformers, and multimodal architectures to real-world datasets
• Experimenting with novel architectures, loss functions, and training strategies
• Performing error analysis and model interpretability investigations
• Contributing to research discussions, technical documentation, and model deployment pipelines

Qualifications

• Current Master’s or PhD student in Computer Science, Electrical Engineering, or related field
• Strong foundation in machine learning and computer vision
• Experience with CNNs, Transformers, or related deep learning architectures (LLM or multimodal experience is a plus)
• Strong Python programming skills. Hands-on experience with PyTorch or TensorFlow
• Demonstrated problem-solving ability and experience running technical or research projects
• Clear written and verbal communication skills