Member of Technical Staff (machine Learning Engineer, Search)

at Perplexity · AI Frontier · Belgrade, Serbia · Search

Machine Learning Engineer focused on building and deploying search technologies, including retrieval, ranking, and RAG pipelines, with a focus on LLMs.

What you'd actually do

  1. Relentlessly push search quality forward—through models, data, tools, or any other leverage available
  2. Architect and build core components of our search platform and model stack
  3. Train and evaluate retrieval, ranking and classification models, including LLMs
  4. Deploy models - from boosting to LLMs - in a scalable and performant way
  5. Build and optimize RAG pipelines for grounding and answer generation

Skills

Required

  • search and retrieval systems
  • quality evaluation principles and metrics
  • large-scale search or recommender systems
  • LLMs
  • RAG pipelines

Nice to have

  • Data
  • AI
  • Infrastructure
  • Product teams

What the JD emphasized

  • Minimum of 5 years of working on search or recsys-related projects

Other signals

  • building core components of search platform and model stack
  • training and evaluating retrieval, ranking and classification models, including LLMs
  • deploying models in a scalable and performant way
  • building and optimizing RAG pipelines
Read full 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