Tech Stack

Description

You will work closely with experienced ML researchers and engineers on cutting-edge research at the intersection of computer vision and sequence modeling. Your work includes designing and experimenting with new ML architectures for structured visual data, evaluating alternative modeling paradigms, and investigating techniques for improving robustness and generalization. This internship offers opportunities for novel model design and potential real-world impact.

Requirements

• MSc or PhD student in Computer Science, ML, AI, or related field with strong research focus
• Proficiency in Python and deep learning frameworks such as PyTorch
• Practical experience designing, training, and evaluating neural networks (CNNs, Transformers)
• Strong analytical and problem-solving abilities, with capability to interpret experimental results
• Familiarity with research best practices including reproducibility and controlled experiments

Responsibilities

• Design and experiment with new ML architectures for structured visual data
• Evaluate alternative modeling paradigms (encoder-decoder, hybrid Transformer models, sequence-based representations)
• Investigate techniques for improving robustness, generalization, and multi-view reasoning
• Run systematic experiments, ablations, and error analyses to validate research hypotheses