Information Retrieval Engineer

ADOBE

Base: $125,600 - $234,150 annually (us); californi...
Hybrid
4+ years in data engineering or ml infrastructure
Experience building rag pipelines
Strong python programming skills
This role focuses on architecting scalable retrieval pipelines using vector databases to power context-aware large language models

Job Summary

  • This role focuses on architecting scalable retrieval pipelines using vector databases to power context-aware large language models.
  • Candidates will implement hybrid retrieval systems combining semantic search and keyword matching to ensure high-quality information access.
  • The position requires continuous improvement of retrieval relevance through experimentation and monitoring to align with downstream model behavior.

Matching Summary

This role focuses on architecting scalable retrieval pipelines using vector databases to power context-aware large language models.

Salary

Base: $125,600 - $234,150 annually (US); California range: $161,700 - $234,150; Short-term incentives via Annual Incentive Plan (AIP)

Skills & Requirements

Must-have

  • 4+ years in data engineering or ML infrastructure
  • Experience building RAG pipelines
  • Strong Python programming skills
  • Proficiency with vector databases like FAISS or Pinecone
  • Knowledge of embedding models and document indexing

Nice-to-have

  • Experience with graph databases like Neo4j
  • Background in Information Retrieval or NLP
  • Familiarity with MLOps tooling such as Airflow
  • Optimization experience for LLMs like OpenAI or Anthropic

Key Requirements

  • Bachelor's or Master's degree in Computer Science or related field
  • 4+ years of experience in data engineering, ML infrastructure, or information retrieval
  • Proven track record deploying semantic search systems

Work Rights

Not specified

Tailored Resume

Cover Letter