ML Research Engineer Intern — Retrieval & RAG Pipelines

Perplexity; United States; Remote; USD 34,440,000 - 48,216,000; Full time

Job summary

Perplexity is seeking a Machine Learning Research Engineer Intern to optimize deep learning models for search quality. You will train large-scale models using PyTorch and apply distributed training techniques to improve retrieval-based systems.

The role emphasizes research in representation learning and building retrieval and ranking models, including retrieval-augmented generation (RAG) pipelines. This internship offers hands-on experience in cutting-edge search technology.

Qualifications

• Solid foundation in PyTorch and an interest in representation learning.
• Experience with training large-scale deep learning models is a plus.
• Familiarity with retrieval and ranking concepts is beneficial.

Responsibilities

• Optimize deep learning models to improve search quality.
• Train large-scale models using PyTorch and distributed training techniques.
• Contribute to training and evaluating retrieval and ranking models, including RAG pipelines.

Skills

Deep learning

Representation learning

Distributed training

Tools

PyTorch

Job description

Perplexity is seeking a Machine Learning Research Engineer Intern to optimize deep learning models for search quality. You will train large-scale models using PyTorch and apply distributed training techniques to improve retrieval-based systems.

The role emphasizes research in representation learning and building retrieval and ranking models, including retrieval-augmented generation (RAG) pipelines. This internship offers hands-on experience in cutting-edge search technology.