Perplexity Search Machine Learning Engineer Internship 2026: Eligibility, Responsibilities, Location and Application Details
Perplexity is offering a Search Machine Learning Engineer Intern opportunity in its Search department in London. The internship is a full-time position focused on building and improving search technologies, particularly information retrieval and ranking.
Interns will work alongside experienced engineers on search-quality experiments, machine learning models, retrieval and ranking systems, RAG pipelines, and production ML infrastructure. The program runs for 12 to 24 weeks and is conducted full-time and in person at the London office.
The role is designed for candidates with a strong foundation in machine learning and statistics, along with practical experience in Python and machine learning frameworks. Experience in search, recommendation systems or NLP is advantageous but is not mandatory.
Perplexity Search ML Engineer Intern: Overview
| Particular | Details |
|---|---|
| Company | Perplexity |
| Position | Search Machine Learning Engineer Intern |
| Department | Search |
| Job Type | Internship |
| Employment Type | Full Time |
| Location | London |
| Work Mode | In-person |
| Internship Duration | 12–24 weeks |
| Primary Focus | Search, Retrieval and Ranking |
| Experience | Not explicitly required |
| Key Programming Language | Python |
| ML Frameworks | PyTorch, TensorFlow, JAX |
| Additional Skill | Rust is a plus |
About the Internship
The Search Machine Learning Engineer Intern will contribute to the development of advanced search technology. The position focuses on improving how users search for and discover information through better retrieval, ranking, classification and answer-generation systems.
Interns will work closely with experienced engineers and have the opportunity to contribute to experiments and production-oriented ML projects.
The internship is full-time and in person in London’s Perplexity office and lasts between 12 and 24 weeks.
What Will a Search Machine Learning Engineer Intern Do?
The role covers several stages of the machine learning and search-development lifecycle.
Improve Search Quality
Interns will contribute to experiments aimed at improving search quality through:
- Better machine learning models
- More effective use of data
- Improved evaluation tools
This work will be carried out under the guidance of senior engineers.
Build Retrieval and Ranking Components
The intern will help design and implement components of the search platform and model stack, including:
- Retrieval models
- Ranking models
- Classification models
These systems form key parts of modern search and information-discovery experiences.
Train and Evaluate Models
The role involves training and evaluating models for retrieval, ranking and classification tasks.
The description specifically includes LLM-based approaches, giving interns exposure to modern language-model techniques applied to search.
Deploy and Monitor Search Models
Interns will support the deployment and monitoring of search and ranking models. The goal is to help ensure these systems operate in a scalable and performant manner.
Work on RAG Pipelines
The internship also involves helping build and improve Retrieval-Augmented Generation (RAG) pipelines used for grounding and answer generation.
Collaborate Across Teams
The intern will collaborate with:
- Data teams
- AI teams
- Infrastructure teams
- Product teams
This cross-functional work is intended to help deliver search improvements quickly while learning production machine-learning practices.
Eligibility for Perplexity Search ML Engineer Internship
The job description emphasizes a strong foundation in machine learning and statistics.
Candidates should have academic coursework or project experience related to areas such as:
- Information retrieval
- Ranking
- Recommender systems
Programming and Machine Learning Skills
Candidates should have experience with Python and common machine-learning frameworks.
The listing gives the following examples:
- PyTorch
- TensorFlow
- JAX
This experience may come from academic work, open-source contributions or personal projects.
Search, Recommendation or NLP Experience
Previous experience with:
- Search
- Recommendation systems
- Natural language processing (NLP)
is considered a plus, but it is not required.
Such experience can come from internships, research or significant personal/academic projects.
Model Evaluation
Familiarity with evaluating model quality using offline metrics and/or A/B testing is advantageous, although the listing states that it is not required.
Personal Qualities
Perplexity is also looking for candidates who are:
- Self-driven
- Curious
- Willing to learn
- Comfortable taking ownership
- Comfortable working in a fast-paced environment
Rust
Experience with Rust is an additional advantage but is not listed as a mandatory requirement.
Internship Duration and Work Arrangement
The internship program lasts 12–24 weeks.
It is:
- Full time
- In person
- Based in the London office
Candidates should therefore be prepared for an in-office internship rather than a remote arrangement.
Selection Process
The supplied job description does not specify the individual stages of Perplexity’s recruitment process for this internship.
It does not provide confirmed details about coding assessments, technical interviews, HR interviews or other selection stages.
Candidates should therefore refer to the application process for any additional recruitment-stage information.
Salary and Benefits
The supplied job description does not provide salary, stipend or benefits information for the internship.
Accordingly, no compensation figure should be assumed from the available information.
How to Apply
Candidates interested in the Search Machine Learning Engineer Internship can apply through the Perplexity careers application page associated with the vacancy.
The supplied listing provides separate Overview and Application pages for the position.
Candidates should review the application requirements carefully and submit the information requested through the official application channel.
Important Points Before Applying
- The position is a Search Machine Learning Engineer Intern role.
- The department is Search.
- The position is based in London.
- The internship is full time and in person.
- The program duration is 12–24 weeks.
- The work focuses heavily on retrieval, ranking and search quality.
- Strong foundations in machine learning and statistics are expected.
- Python experience is required.
- Experience with PyTorch, TensorFlow or JAX is relevant.
- Search, recommendation or NLP experience is helpful but not mandatory.
- Knowledge of offline model evaluation or A/B testing is a plus.
- Rust experience is a plus.
- The role includes work involving LLM-based model evaluation and RAG pipelines.
- Salary and benefits are not specified in the supplied listing.
Frequently Asked Questions
What is the Perplexity Search Machine Learning Engineer Internship?
It is a full-time machine-learning internship in the Search department focused on retrieval, ranking, classification, search quality and related ML systems.
Where is the internship located?
The internship is based in London and is conducted in person at the Perplexity office.
How long is the Perplexity internship?
The internship program lasts 12 to 24 weeks.
Is the internship remote?
No. The supplied listing states that the program is full-time and in person in the London office.
What programming language is required?
The qualifications specify experience with Python. Experience with Rust is considered a plus.
Which machine-learning frameworks are mentioned?
The listing mentions PyTorch, TensorFlow and JAX as examples of common ML frameworks.
Is previous search or NLP experience mandatory?
No. Previous experience in search, recommendation or NLP is described as a plus rather than a requirement.
Is knowledge of A/B testing required?
No. Familiarity with offline metrics and/or A/B testing is listed as advantageous but not required.
What areas of machine learning will the intern work on?
The role covers retrieval, ranking, classification, model evaluation, search-quality experimentation, production model deployment and monitoring, and RAG pipelines.
Does the job listing mention a salary?
No. The supplied description does not specify a salary or internship stipend.