
Internship - Search Machine Learning Engineer
at Perplexity AI
Posted 5 hours ago
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**Intern - Search Machine Learning Engineer**: Collaborate with senior engineers to enhance search quality by experimenting with new models and tools. Key responsibilities include contributing to search experiments, designing and implementing search platform components, training evaluation models (LLM-based), deploying ranking models, and improving RAG pipelines. Ideal candidate should have entry-level experience in machine learning and search technologies, including familiarity with ranking, retrieval, and classification models. This is a full-time, on-site 12-24 week internship in Belgrade.
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 Belgrade office.
Responsibilities:
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.
Qualifications:
Strong foundation in machine learning and statistics, with coursework or projects related to information retrieval, ranking, or recommender systems.
Experience with Python and common ML frameworks (e.g. PyTorch, TensorFlow, JAX) through academic, open source, or personal projects.
Familiarity with evaluating model quality using offline metrics and/or A/B testing is a plus, but not required.
Previous experience (internships, research, or significant projects) working on search, recommendation, or NLP is a plus, but not required.
Self-driven and curious, with a strong sense of ownership, willingness to learn, and comfort working in a fast-paced environment
Experience with Rust will be a plus
