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AI Code Search and Retrieval Engineer

Joseph Kim

Full-time · Job · Los_Angeles

About the role

Stack Overflow's 'how do I do X in Python' worked when codebases were small. When your codebase is 8 million lines of proprietary code, the question isn't 'how do I do X' — it's 'where in our codebase is X already done, and what are the 14 callers of the function that does it.' That's code search, and keyword search fails because variable names describe implementation choices, not intent. We build developer intelligence tooling, and code search is the highest-impact capability we don't have yet. You'll design the semantic code search system: fine-tuning code embedding models on our clients' codebases, building retrieval pipelines that find semantically similar functions and modules, and implementing the reranking logic that surfaces the most relevant results for each developer's context. The output plugs into IDE extensions used by 80,000 developers daily. This is a senior IC role at the frontier of code intelligence. The academic literature on code embeddings is developing fast — you'll need to stay current and implement findings that have production legs, not just benchmark numbers.

Responsibilities

  • Design and fine-tune code embedding models for semantic code search
  • Build retrieval pipelines supporting function-level and file-level search
  • Implement reranking models incorporating developer context and usage patterns
  • Create evaluation benchmarks measuring search relevance on real codebases
  • Optimize retrieval latency to meet IDE integration requirements
  • Integrate search capabilities into existing IDE extension APIs

Requirements

  • 6+ years in ML engineering with NLP, information retrieval, or code intelligence experience
  • Deep expertise in embedding models and RAG architectures
  • Familiarity with code representation learning and program analysis
  • Strong Python and HuggingFace skills
  • Experience fine-tuning models on domain-specific corpora

Benefits

  • Fully remote with flexible schedule
  • Top-of-market compensation
  • Comprehensive health benefits
  • $5,000 annual conference and learning budget
  • Equity participation

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Categories

AI & Machine Learning Engineers NLP & Prompt Engineering

Skills

python pytorch hugging face rag docker

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

AI & Machine Learning Engineers NLP & Prompt Engineering

Skills

python pytorch hugging face rag docker fastapi

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