Principal NLP Engineer for Enterprise AI & Copilots

Teradata; Honolulu (HI); Hybrid; USD 183,000 - 274,000; Full time

Job summary

Teradata seeks a Principal NLP Engineer to lead design, development and deployment of NLP, knowledge graphs, and enterprise copilots within the Context Engine platform. You will bridge research and production, shaping architectures that scale to millions of users and billons of documents.

You will own roadmap, mentor engineers, and drive innovations in retrieval, grounding, and multimodal understanding across on-prem, cloud, and hybrid environments.

Qualifications

• PhD or MS in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, NLP, or related field.
• 12+ years of software engineering experience, including 8+ years building production NLP and ML systems.
• Recognized industry leader in Natural Language Processing, Language AI, Search, Retrieval, or LLM-based systems.

Responsibilities

• Define and execute the strategic roadmap for NLP and language understanding capabilities across our Knowledge Platform.
• Serve as the technical authority for large-scale NLP architecture, algorithms, and production deployment.
• Drive innovation in enterprise language understanding, semantic search, retrieval systems, knowledge extraction, and AI reasoning.
• Mentor senior engineers and help establish NLP engineering best practices across the company.

Skills

Python

PyTorch

TensorFlow/JAX

Spark

Distributed ML

HuggingFace

Fine-tuning

NLP systems

Knowledge graphs

Education

PhD/MS in CS/AI/NLP

Tools

Hugging Face

Spark

TensorFlow

PyTorch

Job description

Teradata seeks a Principal NLP Engineer to lead design, development and deployment of NLP, knowledge graphs, and enterprise copilots within the Context Engine platform. You will bridge research and production, shaping architectures that scale to millions of users and billons of documents.

You will own roadmap, mentor engineers, and drive innovations in retrieval, grounding, and multimodal understanding across on-prem, cloud, and hybrid environments.