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 modeling paradigms, and conducting systematic experiments to validate research hypotheses.

Requirements

• MSc or PhD student in Computer Science, ML, AI, or related field
• Proficiency in Python and PyTorch
• Practical experience with CNNs and Transformer-based architectures
• Strong analytical and problem-solving abilities
• Familiarity with research best practices

Responsibilities

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