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NLP Engineer

Emma Garcia

Full-time · Job · London

About the role

Our data pipelines are growing faster than our team. We process over 4 million legal documents a month for enterprise clients across Europe, and our NLP stack is the backbone of everything we deliver. We need an engineer who can push our text extraction and classification systems to the next level. Right now, we're migrating from rule-based parsers to transformer-based models fine-tuned on domain-specific corpora. You'll work alongside two senior engineers and a linguist to build, evaluate, and ship these models. We use Hugging Face for training, LangChain for orchestration, and RAG pipelines for context-aware document Q&A. The codebase is clean, the deployments are automated, and the problems are genuinely hard. If you enjoy the craft of making language models work reliably on messy real-world text, you'll thrive here.

Responsibilities

  • Build and fine-tune transformer models for legal document classification
  • Design RAG pipelines for context-aware document retrieval
  • Collaborate with the linguistics team on annotation strategy and data quality
  • You'll spend most of your time iterating on model performance and debugging edge cases
  • Maintain evaluation frameworks to track model accuracy over time

Requirements

  • 3+ years working with NLP models in production
  • Hands-on experience with Hugging Face Transformers and PyTorch
  • Familiarity with RAG architectures and LangChain
  • Strong SQL skills for data analysis
  • Experience working with unstructured text data at scale

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Categories

NLP & Prompt Engineering AI & Machine Learning Engineers

Skills

python hugging face pytorch langchain rag

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

NLP & Prompt Engineering AI & Machine Learning Engineers

Skills

python hugging face pytorch langchain rag sql

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