Search Machine Learning Engineer Intern

Perplexity AI; Greater London; On-site; GBP 17,000 - 22,000; Full time

Job summary

Perplexity AI in London is seeking a Search ML Engineer Intern to help build the next generation of search technologies, focusing on retrieval and ranking. You will work closely with experienced engineers to improve search quality and ship features that directly impact how users search and discover information.

The internship program runs 12–24 weeks full-time, in-person at the London office. You will design and implement components of the search platform, train evaluation models (LLM-based

Qualifications

• Strong foundation in ML and statistics with information retrieval or ranking coursework.
• Experience evaluating models using offline metrics.
• Familiarity with A/B testing is a plus.
• Self-driven, ownership and ability to work in a fast-paced environment.
• Internship duration: 12–24 weeks, full-time, in London.

Responsibilities

• Design and implement components of the search platform and model stack (retrieval, ranking, classification).
• Train and evaluate models for retrieval, ranking, and classification tasks (including LLM-based approaches).
• Support deployment and monitoring of search and ranking models in production.
• Help build and iterate on RAG pipelines for grounding and answer generation.
• Collaborate with Data, AI, Infrastructure and Product teams to deliver improvements quickly.

Skills

Python

ML frameworks

Information retrieval

Ranking

Recommender systems

Rust

Tools

PyTorch

TensorFlow

JAX

Job description

• Perplexity is looking for a Search Machine Learning Engineer Intern to help build the next generation of advanced search technologies, with a focus on retrieval and ranking
• You will work closely with experienced engineers to improve search quality, experiment with new models, and ship features that directly impact how users search and discover information
• Internship program: 12 - 24 weeks, full-time, in-person in the London office
• Contribute to experiments that improve search quality through better models, data usage, and evaluation tools, under the guidance of senior engineers
• Design and implement components of the search platform and model stack, including retrieval, ranking, and classification models
• Train evaluating models (including LLM-based approaches) for retrieval, ranking, and classification tasks
• Support deployment and monitoring of search and ranking models in a scalable and performant way
• Help build and iterate on RAG pipelines for grounding and answer generation
• Collaborate with Data, AI, Infrastructure and Product teams to deliver improvements quickly and learn best practices in production ML

Experience with Python and common ML frameworks (e.g. PyTorch, TensorFlow, JAX) through academic, open source, or personal projectsSelf-driven and curious, with a strong sense of ownership, willingness to learn, and comfort working in a fast-paced environmentStrong foundation in machine learning and statistics, with coursework or projects related to information retrieval, ranking, or recommender systemsExperience with Rust will be a plusPrevious experience (internships, research, or significant projects) working on search, recommendation, or NLP is a plus, but not requiredFamiliarity with evaluating model quality using offline metrics and/or A/B testing is a plus, but not required