18:I[34901,["/_next/static/chunks/1q_xs299ft_73.js","/_next/static/chunks/1hsg494-jz4os.js","/_next/static/chunks/1a25lc5cxtp8a.js","/_next/static/chunks/08v7mhpebw2l_.js"],"JobTable"] 19:Ta08,

Perplexity is looking for a Backend/Infrastructure Engineer Intern to support our small, high-impact team building the systems that power our search experience. You will work closely with experienced engineers to help design, build, and operate robust infrastructure and backend services that keep Perplexity fast, reliable, and scalable.

Internship program: 12 - 24 weeks, full-time, in-person in the Belgrade office.

Responsibilities:

Build and maintain infrastructure that supports high-performance search systems, with mentorship from senior engineers.

Design internal tools and automation to improve developer workflows and operational efficiency.

Support the design, deployment, and monitoring of cloud-native systems on AWS.

Contribute to improving CI/CD pipelines, testing infrastructure, and release processes.

Debug and optimize Linux-based services, containers, and backend systems.

Contribute to product codebases, primarily using Rust, Go or C++.

Qualifications:

Working towards a degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Familiarity with at least one programming language such as Go, Rust, or C/C++, through coursework or projects.

Basic understanding or exposure to cloud infrastructure (e.g. AWS) and Linux systems is a plus, not a requirement.

Interest in infrastructure, distributed systems, or backend engineering, with willingness to learn about CI/CD, monitoring, and performance.

A proactive and curious learner who enjoys collaborating in a fast-paced, innovative environment

1a:Tac8,

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.

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

1b:Tab9,

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

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Role	Company	Location	Season	Posted
Internship - Search Backend Infra Engineer	Perplexity	Belgrade	—	2 months ago
Internship - Search Machine Learning Engineer	Perplexity	London	—	5 months ago
Internship - Search Machine Learning Engineer	Perplexity	Belgrade	Summer 2026	7 months ago