Machine Learning Engineer Intern

Machine Learning Engineer InternCommitment Period: Jan 2027 onwards (minimum 6 months, full time)Job Description:We are looking for a ML Engineer Intern to research and build methods that find best compressed neural networks. Focus of this work includes knowledge distillation (KD) and quantization-aware distillation (QAD).Deliverable: a comparison of techniques by model family, with reported recommendations.

Responsibilities

Develop KD and QAD approaches across different model typesAblate key choices among various techniquesBuild reproducible training and evaluation scripts, and report findingsTechniques You Will Work OnKnowledge distillation: soft-label, feature-based and self-distillationQuantization-aware training (QAT) and QADLow-bit quantization with post-training quantization (PTQ) as the baseline

Requirements

Currently studying CS, Engineering, AI/ML or a related fieldCommitment for at least 6 months full timeStrong Python and hands-on PyTorch (custom training loops and losses)Trained and evaluated vision models end to endKnowledge of KD and quantization basics (temperature, PTQ vs QAT)Careful, reproducible experiments and clear written reportsPreferred (Plus):Project or thesis on model compression (quantization)Experience with PyTorch quantization tools or ONNX exportPublications at leading conferences (i.e. CVPR, ICML, NeurIPS etc.)