NLP Engineer
Syntax Technologies
full-time
Posted on:
Location Type: Remote
Location: United States
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About the role
- Pipeline Development: Design and build end-to-end text extraction pipelines for policy, regulatory, fintech, and healthcare documents
- Entity & Clause Extraction: Extract key entities (countries, companies, minerals) and structure policy clauses and obligations
- Deep Learning & Transformers: Fine-tune BERT / RoBERTa for NER, text classification, and relation extraction tasks
- LLM Integration: Leverage LLM APIs with structured output extraction, prompt engineering, and tool/function calling
- Data Engineering: Build scalable Python pipelines for high-volume document processing with robust pre-processing for PDF, DOCX, and HTML
- Schema & Graph Readiness: Define and enforce JSON schemas; ensure outputs are clean and compatible with knowledge graph ingestion
- Accuracy Improvement: Evaluate model performance, track metrics, and implement feedback loops to improve extraction quality over time
Requirements
- 3–5 years hands-on NLP engineering real production pipelines, not just model experiments
- Strong Python skills: OOP, async programming, packaging, and testing
- NLP frameworks: spaCy, HuggingFace Transformers, NLTK
- Deep learning: fine-tuning transformer models for sequence labeling and classification
- LLM API integration: prompt engineering, structured outputs, and function/tool calling
- Data pipeline experience: ETL, batch processing, and text pre-processing at scale
- JSON schema design and validation using pydantic or json schema
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonNLP engineeringdeep learningtransformer modelstext extractionentity extractiontext classificationdata pipelineJSON schema designETL