Overview

Posted
2 weeks ago
Internship Type
Unclear
Remote Status
On-site
Location
Berlin, DE
Education Level
Unclear
Education Status
Not specified
Field of Study
Not specified
Categories
Machine Learning / AI Engineering
Skills
Pytorch Distributed Training DeepSpeed FSDP Retrieval Systems Evaluation Metrics Representation Learning Contrastive Learning Multilingual Modeling RAG Pipelines
Tags
Not specified

Internship Program Berlin

Internship program: 12 - 24 weeks, full-time, in-person in the Berlin office.

Responsibilities

  • Relentlessly push search quality forward — through models, data, tools, or any other leverage available.

  • Train, and optimize large-scale deep learning models using frameworks like PyTorch, leveraging distributed training (e.g., PyTorch Distributed, DeepSpeed, FSDP) and hardware acceleration, with a focus on retrieval and ranking models.

  • Conduct research in representation learning, including contrastive learning, multilingual, evaluation, and multimodal modeling for search and retrieval.

  • Build and optimize RAG pipelines for grounding and answer generation.

Qualifications

  • 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).