Principal NLP Scientist

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🔥 1 minute ago

🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

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Sourceability

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2015

🤝 B2B

🛍️ eCommerce

🔧 Hardware

B2B • eCommerce • Hardware

Sourceability is a global electronic components distributor and supply-chain solutions provider. It operates Sourcengine, an e-commerce marketplace for professional buyers and engineers, and provides digital tools such as Datalynq (data & analytics) and Quotengine for RFQs and quoting. The company emphasizes transparency, quality control, and logistics services, maintains a large catalog (1+ billion parts, 40+ franchise lines, 3,500+ suppliers), and has a global footprint (15 countries, 22 locations, 350+ employees). Sourceability serves professional buyers and engineers with sourcing, distribution, QC, and analytics to streamline electronic components procurement.

📋 Description

• Design, research, and improve advanced Natural Language Processing and Large Language Model capabilities for production business systems • Lead NLP solutions for named entity recognition, text classification, text generation, semantic search, information extraction, and language-driven automation • Define technical direction for NLP systems and evaluate new approaches • Design experiments, create prototypes, and move successful models into production • Collaborate with software engineers, data engineers, product managers, analysts, and data annotation teams • Improve automation quality, data processing accuracy, operational efficiency, and long-term AI capabilities • Review existing models, datasets, annotation processes, and production use cases • Identify high-impact NLP and LLM improvement opportunities • Define evaluation metrics and create a technical roadmap for NER, classification, generation, and information extraction • Establish standards for data labeling quality, model validation, and production readiness • Deliver prototypes or improvement proposals with measurable business value • Provide scientific and technical direction for NLP and LLM capabilities and expert guidance 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 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, including RNN, CNN, Transformer-based architectures, attention mechanisms, embeddings, fine-tuning strategies, layers, modules, and loss functions • Strong practical experience with NLP tasks such as NER, classification, text generation, semantic similarity, information extraction, and document understanding • Strong experience with Large Language Models, including model evaluation, prompt design, fine-tuning, retrieval-augmented generation, and safe production usage • Practical understanding of RAG, GraphRAG, knowledge graphs, embeddings, and hybrid retrieval approaches for production LLM applications • 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 Pandas, NumPy, SciPy, scikit-learn, and Matplotlib • Experience working with SQL databases and structured business data • Experience with cloud platforms such as 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 requiring formal people management authority • Preferred: experience leading NLP or AI research initiatives in a commercial production environment • Preferred: experience with multilingual NLP systems • Preferred: experience with vector databases, embeddings, semantic search, and RAG architectures • Preferred: experience 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: experience with MLOps practices and CI/CD for machine learning systems • Preferred: experience working with data annotation teams and creating annotation instructions • Preferred: experience with .NET / C#, ASP.NET Core, or ML service integration into enterprise software platforms • Preferred: experience building prototypes, demos, and proof-of-concept applications • Publications, patents, or recognized technical contributions are a plus

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