Role overview
**Machine Learning Engineer – NLP & AI Systems**
Remote (Must be based in USA)
$160k - $200k Base
**About the Company:**
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.
**Responsibilities:**
* 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.
**Qualifications:**
* 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.
**Bonus:**
* 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.