Internship - Search Machine Learning Engineer
London · London, United Kingdom
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Search — team source
Department: Search
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Will you now or in the future require sponsorship for employment visa status in the United Kingdom, Germany or Serbia?
From the employer’s application form
What you’ll work on
Full postingRun experiments to improve search quality through better models, data, and evaluation tools
Design and implement parts of the search platform and model stack
Train and evaluate retrieval, ranking, and classification models, including LLM-based ones
Help deploy and monitor search and ranking models at scale
Help build and iterate on RAG pipelines for grounding and answer generation
From the employer’s posting
Contribute to experiments that improve search quality through better models, data usage, and evaluation tools
Design and implement components of the search platform and model stack
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.
What you’ll bring
All qualificationsCore experience
- Experience with Python and common ML frameworks (e.g.
Preferred experience
- Familiarity with evaluating model quality using offline metrics and/or A/B testing is a plus, but not required.
- Experience with Rust will be a plus
Qualification wording
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.
Experience with Rust will be a plus
Tools in this posting
- Python
- Rust
- PyTorch
- TensorFlow
Source — Tool mentions in context
- 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.
- 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
Posting record
Report an errorOpen 4 monthsWe first saw this posting 149 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 2, 2026 · 149 days ago
- Recorded sightings
- 261
- Last seen by us
- Oct 30, 2026
- Employer says posted
- Apr 8, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
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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.
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
Source details
Source notes
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- Pay
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- Location & working pattern
London, United Kingdom
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