Principal NLP Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, research, and enhance advanced Natural Language Processing and Large Language Model capabilities for operational business systems.

• Lead NLP initiatives for named entity recognition, text classification, text generation, semantic search, information extraction, and language-driven automation.

• Establish the technical direction for NLP systems and assess new methodologies.

• Conduct experiments, develop prototypes, and transition successful models to production.

• Collaborate with software engineers, data engineers, product managers, analysts, and data annotation teams.

• Enhance automation quality, data processing accuracy, operational efficiency, and long-term AI capabilities.

• Review current models, datasets, annotation processes, and production use cases.

• Identify opportunities for significant improvements in NLP and LLM.

• Define evaluation metrics and develop a technical roadmap for NER, classification, generation, and information extraction.

• Set standards for data labeling quality, model validation, and production readiness.

• Deliver prototypes or proposals for improvements that provide measurable business value.

• Provide scientific and technical leadership for NLP and LLM capabilities, along with expert advice on technical feasibility, reliability, and production readiness.

⛳️ Requirements

• PhD in Computer Science, Machine Learning, Artificial Intelligence, Computational Linguistics, Applied Mathematics, Data Science, or a closely related technical discipline.

• Over 8 years of professional experience in machine learning, artificial intelligence, or NLP.

• More than 5 years of practical experience in developing NLP models for production or near-production systems.

• Extensive knowledge of modern neural network architectures, including RNN, CNN, Transformer-based architectures, attention mechanisms, embeddings, fine-tuning strategies, layers, modules, and loss functions.

• Strong practical experience in NLP tasks such as NER, classification, text generation, semantic similarity, information extraction, and document understanding.

• Significant experience with Large Language Models, including model evaluation, prompt design, fine-tuning, retrieval-augmented generation, and secure production usage.

• Practical understanding of RAG, GraphRAG, knowledge graphs, embeddings, and hybrid retrieval methods for production LLM applications.

• Extensive hands-on experience with Python.

• Strong experience with PyTorch and Hugging Face Transformers.

• Familiarity with ONNX or other model optimization/model serving formats.

• Comprehensive understanding of data preparation, data quality, labeling workflows, annotation guidelines, and model evaluation metrics.

• Practical experience with Pandas, NumPy, SciPy, scikit-learn, and Matplotlib.

• Experience in working with SQL databases and structured business data.

• Familiarity with cloud platforms like Microsoft Azure or AWS.

• Ability to design experiments, define success metrics, compare model approaches, and clearly articulate trade-offs.

• Strong written and verbal communication skills in English.

• Experience working in Agile engineering environments.

• Capability to provide technical leadership without needing formal people management authority.

• Preferred: experience in leading NLP or AI research projects in a commercial production context.

• Preferred: experience with multilingual NLP systems.

• Preferred: experience with vector databases, embeddings, semantic search, and RAG architectures.

• Preferred: familiarity with knowledge graph concepts and graph databases such as Neo4j or FalkorDB.

• Preferred: experience with model serving, monitoring, drift detection, and production ML observability.

• Preferred: experience with Docker and containerized ML workloads.

• Preferred: knowledge of MLOps practices and CI/CD for machine learning systems.

• Preferred: experience collaborating with data annotation teams and creating annotation guidelines.

• Preferred: experience with .NET / C#, ASP.NET Core, or integrating ML services into enterprise software platforms.

• Preferred: experience in building prototypes, demos, and proof-of-concept applications.

• Publications, patents, or recognized technical contributions are advantageous.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health benefits including medical, dental, and vision coverage.

• Opportunities for professional development and continuous learning.

• Flexible working hours and remote work options.

• Collaborative and innovative work environment.