Internship - Machine Learning Research Engineer

Perplexity

Berlin · Full-time · Posted 1 month ago

Apply on Perplexity's site

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).

At a glance on RemoteAI

132 reviewed professionals on RemoteAI match this role at 70% or more.
PyTorch: 716 of 3,523 reviewed AI professionals on RemoteAI list it (20%) — the most common skill this role asks for.
RAG: 602 of 3,523 reviewed AI professionals on RemoteAI list it (17%).
Machine Learning : 228 of 3,523 reviewed AI professionals on RemoteAI list it (6%).
Perplexity has 14 other open roles on RemoteAI.

Create a free profile to see your own match score for this role.