Search Machine Learning Engineer Internship

About the role

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.

Key responsibilities

• Contribute to experiments that improve search quality through better models, data usage, and evaluation tools, under senior guidance.
• Design and implement components of the search platform and model stack, including retrieval, ranking, and classification models.
• Train and evaluate models (including LLM‑based approaches) for retrieval, ranking, and classification tasks.
• Support deployment and monitoring of search and ranking models in a scalable, 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 production ML best practices.

Required profile

• Strong foundation in machine learning and statistics, demonstrated through coursework or projects related to information retrieval, ranking, or recommender systems.
• Experience with Python and common ML frameworks such as PyTorch, TensorFlow, or JAX.
• Familiarity with evaluating model quality using offline metrics or A/B testing (a plus).
• Previous experience working on search, recommendation, or NLP projects (a plus).
• Self‑driven, curious, and comfortable taking ownership in a fast‑paced environment.
• Comfortable communicating in English and collaborating in a professional setting.

Required skills

• Python
• PyTorch
• TensorFlow
• JAX
• Rust (optional but beneficial)