Remote NLP Data Scientist for LLM & RAG

The Rawlings Group; United States; Remote; USD 180,000 - 230,000; Full time

Benefits offered by this job

Work from anywhere in the US

Medical/Dental/Vision

FSA/HSA

Tuition reimbursement

401(k) with company match

Unlimited PTO

Health and wellness benefits

Job summary

Machinify, a leading healthcare intelligence company, is hiring a Data Scientist focused on natural language processing to transform unstructured text into product features and business insight. You will own problems end-to-end—from framing and data to modeling, evaluation, and shipping—working closely with engineering and product to deploy in users' hands.

You will design and train NLP models for classification, extraction, retrieval, and summarization; fine-tune LLMs, build robust evaluation

Qualifications

• 3+ years of applied ML experience with a meaningful portion in NLP.
• Strong Python and the modern NLP stack including PyTorch or JAX, Hugging Face Transformers, spaCy, sentence-transformers.
• Hands-on experience fine-tuning transformer models and/or building production RAG systems.

Responsibilities

• Design and train NLP models for classification, entity extraction, retrieval, summarization, and semantic search.
• Fine-tune and evaluate LLMs; build RAG pipelines and agentic workflows where appropriate.
• Build robust evaluation harnesses with offline metrics, human-in-the-loop review, and online A/B tests.
• Partner with ML engineers to productionize models (latency, cost, monitoring).
• Turn ambiguous product questions into well-scoped ML problems and communicate tradeoffs.

Skills

Applied ML/NLP

Python

PyTorch

Hugging Face Transformers

spaCy

sentence-transformers

Tools

pgvector

Pinecone

Weaviate

Job description

Machinify, a leading healthcare intelligence company, is hiring a Data Scientist focused on natural language processing to transform unstructured text into product features and business insight. You will own problems end-to-end—from framing and data to modeling, evaluation, and shipping—working closely with engineering and product to deploy in users' hands.

You will design and train NLP models for classification, extraction, retrieval, and summarization; fine-tune LLMs, build robust evaluation