Harnham
AI

NLP Engineer Remote USA $160k $200k Base

Harnham · · $160k - $200k

Actively hiring Posted 3 months ago

Role overview

We’re a fast-growing AI company transforming one of the world’s largest and most operationally complex industries through intelligent automation. The organization is backed by leading investors and is scaling rapidly, with a team of engineers, data scientists, and domain experts focused on embedding AI directly into real-world workflows.

Our mission is to digitize and automate field operations by building production-ready AI agents that handle document understanding, question answering, and decision support at scale. The team blends deep technical expertise with hands-on industry experience, and we’re now expanding our applied AI capabilities during a critical phase of growth.

What you'll work on

  • Build and enhance search and retrieval systems using advanced NLP and information retrieval techniques.
  • Process and analyze multi-format documents (text, tables, images) to extract and structure key insights.
  • Design and implement entity extraction , relationship modeling , and text classification pipelines.
  • Develop efficient indexing and embedding strategies to power high-performance semantic search.
  • Conduct experiments to evaluate, fine-tune, and improve model accuracy and robustness.
  • Develop and maintain domain-specific language models for specialized use cases.

What we're looking for

  • MS/PhD in Computer Science, NLP, Information Retrieval, or related field .
  • 2+ years of hands-on experience building production-grade NLP or ML systems .
  • Strong proficiency in Python , ML frameworks, and libraries such as spaCy , Hugging Face , or NLTK .
  • Experience with search technologies (e.g., Elasticsearch, graph databases, vector databases).
  • Hands-on experience designing and deploying RAG (Retrieval-Augmented Generation) pipelines , including document retrieval, embedding stores, and LLM integration.
  • Familiarity with LLM-based applications and modern AI toolchains.
  • Experience training or fine-tuning proprietary algorithms.
  • Exposure to agentic AI systems or multi-step reasoning frameworks.
  • Interest in applying AI to real-world operational challenges.

Tags & focus areas

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Fulltime Remote Ai Machine Learning Data Science Nlp Generative Ai