Internship - Machine Learning Research Engineer

Highlights

• Push search quality forward via models, data, and tooling innovation.
• Build and optimize RAG pipelines for grounding and answer generation.
• Research representation learning for multilingual search and retrieval.

Ideal candidate

A curious ML researcher obsessed with search quality and representation learning who loves turning research ideas into real retrieval experiences.

Requirements

• Understanding of search and retrieval systems, including quality evaluation principles and metrics.
• Strong proficiency with PyTorch, including experience in distributed training techniques and performance optimization for large models.
• Interested in representation learning, including contrastive learning, dense & sparse vector representations, representation fusion, cross-lingual representation alignment, training data optimization and robust evaluation.
• Publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, SIGIR).