Lead NLP Scientist for Production LLMs

Sourceability; Austin (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

Sourceability is seeking a Principal NLP Scientist to spearhead the design, evaluation, and deployment of advanced NLP and LLM capabilities across production workflows. You will lead applied research, build multi-domain models, and coordinate with software engineers, data teams, and product managers.

The role emphasizes practical engineering judgment, measurable experiments, and scalable production readiness, influencing how NLP drives automation and data processing quality at scale.

Qualifications

• PhD in a closely related technical field and 8+ years in ML/NLP
• Hands-on experience building NLP models for production or near-production systems (5+ years)
• Strong experience with modern neural architectures (RNN, CNN, Transformer-based) and evaluation methods
• Proven ability to design experiments, define success metrics, and communicate trade-offs clearly

Responsibilities

• Lead design of NLP solutions for NER, text classification, text generation, semantic search, and information extraction
• Bridge research and production by delivering prototypes and production-ready models
• Collaborate with engineers, product managers, and data teams to deploy scalable NLP capabilities
• Evaluate and improve NLP models, including LLM integration and retrieval-augmented generation
• Define data labeling standards and model evaluation metrics for production use

Skills

Python

PyTorch

Transformers

NLP/ML

Prompt design

RAG / GraphRAG

SQL

English communication

Education

PhD in Computer Science / ML / NLP

Tools

Docker

Hugging Face Transformers

Neo4j

Job description

Sourceability is seeking a Principal NLP Scientist to spearhead the design, evaluation, and deployment of advanced NLP and LLM capabilities across production workflows. You will lead applied research, build multi-domain models, and coordinate with software engineers, data teams, and product managers.

The role emphasizes practical engineering judgment, measurable experiments, and scalable production readiness, influencing how NLP drives automation and data processing quality at scale.