Member of Technical Staff (Machine Learning Engineer, Search)

Perplexity; Greater London; On-site; GBP 90,000 - 140,000; Full time

Job summary

Perplexity is seeking an experienced Machine Learning Engineer to help build the next generation of advanced search technologies, with a focus on retrieval and ranking.

The role involves architecting core components of our search platform, training and evaluating retrieval, ranking, and classification models (including LLMs), and deploying scalable models across the stack. Collaboration with cross-functional teams is essential for high-quality delivery.

Qualifications

• 5+ years of working on search or recommender-related projects.
• Deep understanding of search quality evaluation principles and metrics.
• Self-driven with strong ownership and execution.

Responsibilities

• Relentlessly push search quality forward through models, data, or tools.
• Architect and build core components of our search platform and model stack.
• Train and evaluate retrieval, ranking and classification models, including LLMs.
• Deploy models—from boosting to LLMs—in a scalable and performant way.
• Build and optimize RAG pipelines for grounding and answer generation.
• Collaborate with Data, AI, Infrastructure and Product teams to ensure fast delivery.

Skills

Search/retrieval systems

Large-scale search

Recommender systems

Autonomy

Job description

Perplexity is seeking an experienced Machine Learning Engineer to help build the next generation of advanced search technologies, with a focus on retrieval and ranking.

Responsibilities

• Relentlessly push search quality forward—through models, data, tools, or any other leverage available
• Architect and build core components of our search platform and model stack
• Train and evaluate retrieval, ranking and classification models, including LLMs
• Deploy models - from boosting to LLMs - in a scalable and performant way
• Build and optimize RAG pipelines for grounding and answer generation
• Collaborate with Data, AI, Infrastructure and Product teams to ensure fast and high quality delivery

Qualifications

• Deep understanding of search and retrieval systems, including quality evaluation principles and metrics
• Proven track record with large-scale search or recommender systems
• Self-driven, with a strong sense of ownership and execution
• Minimum of 5 years of working on search or recsys-related projects