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Principal NLP Scientist

Sourceability

Location
Global
Workplace
Remote
Employment
Full Time
Salary
—
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Posted 2mo ago

The employer’s full description could not be read from their board. This is a summary of the posting — follow the apply link for the original.

Responsibilities

  • Design, research, and improve NLP and LLM capabilities
  • Lead the design of NLP solutions for NER, text classification, text generation, semantic search, information extraction
  • Make modern NLP and LLM technologies reliable, measurable, maintainable, and useful in production
  • Build and improve systems for named entity recognition and structured data extraction
  • Build and improve systems for text classification and categorization
  • Build and improve systems for text generation and language-based automation
  • Evaluate, adapt, and integrate Large Language Models
  • Implement retrieval-augmented generation and semantic search
  • Develop knowledge graph and GraphRAG-based approaches
  • Oversee data preparation, annotation strategy, and labeling quality
  • Evaluate, monitor, and improve production performance of NLP models
  • Conduct applied NLP research and prototype development
  • Integrate NLP models into internal business applications
  • Define technical direction for NLP systems
  • Evaluate new approaches and design experiments
  • Create prototypes and move successful models into production

Requirements

  • PhD in Computer Science, Machine Learning, Artificial Intelligence, Computational Linguistics, Applied Mathematics, Data Science, or a closely related technical field
  • 8+ years of professional experience in machine learning, artificial intelligence, or NLP
  • 5+ years of hands-on experience building NLP models for production or near-production systems
  • Deep understanding of modern neural network architectures (RNN, CNN, Transformer-based)
  • Strong practical experience with NLP tasks (NER, classification, text generation, semantic similarity, information extraction, document understanding)
  • Strong experience with Large Language Models (evaluation, prompt design, fine-tuning, RAG)
  • Practical understanding of RAG, GraphRAG, knowledge graphs, embeddings, and hybrid retrieval approaches
  • Strong hands-on experience with Python
  • Strong experience with PyTorch and Hugging Face Transformers
  • Experience with ONNX or other model optimization / model serving formats
  • Strong understanding of data preparation, data quality, labeling workflows, annotation guidelines, and model evaluation metrics
  • Practical experience with main data analysis and machine learning libraries (Pandas, NumPy, SciPy, scikit-learn, Matplotlib)
  • Experience working with SQL databases and structured business data
  • Experience with cloud platforms (Microsoft Azure or AWS)
  • Ability to design experiments, define success metrics, compare model approaches, and explain trade-offs clearly
  • Strong written and verbal English communication skills
  • Experience working in Agile engineering environments
  • Ability to provide technical leadership without formal people management authority

Preferred

  • Experience leading NLP or AI research initiatives in a commercial production environment
  • Experience with multilingual NLP systems
  • Experience with vector databases, embeddings, semantic search, and RAG architectures
  • Experience with knowledge graph concepts (entity and relationship modeling, graph schema design, traversal queries, LLM integration with graph databases)
  • Experience with model serving, monitoring, drift detection, and production ML observability
  • Experience with Docker and containerized ML workloads
  • Experience with MLOps practices and CI/CD for machine learning systems
  • Experience working with data annotation teams and creating annotation instructions
  • Experience with .NET / C#, ASP.NET Core, or integration of ML services into enterprise software platforms
  • Experience building prototypes, demos, and proof-of-concept applications for new AI capabilities
  • Publications, patents, or recognized technical contributions in NLP, machine learning, or applied AI are a plus

Skills

  • Python
  • PyTorch
  • Hugging Face Transformers
  • ONNX
  • Pandas
  • NumPy
  • SciPy
  • scikit-learn
  • Matplotlib
  • SQL
  • Azure
  • AWS
  • Docker
  • Neo4j
  • FalkorDB
  • ASP.NET Core
  • C#
  • .NET

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