Lead Data Scientist - NLP & Machine Learning

Lead Data Scientist - NLP & Machine Learning, Fully Remote, £100,000 - £120,000 per annum

Overview

A great client of mine, a leader in the AI space are seeking a highly skilled Lead Data Scientist with a robust background in Natural Language Processing (NLP) and machine learning engineering. This role is pivotal in driving their advanced ML projects-from initial proof-of-concept through full-scale production deployment. The ideal candidate will combine deep technical expertise with a pioneering spirit, capable of transforming open-ended specifications into concrete, scalable solutions.

Key Responsibilities

• Advanced NLP Development:
• Design, build, and deploy NLP models including synthetic data generation, classifier training (SetFit), and fine-tuning large language models (LLMs) using modern techniques like LORA, QLORA, RL.
• Data Modeling & Semantic Analysis:
• Utilise semi-structured data models such as RDF and RDFS within machine learning contexts to enhance data integration and semantic understanding.
• Build RDF-based components for use cases such as semantic similarity and search/retrieval.
• Engineering & Deployment:
• Develop robust APIs and scalable solutions using Fast API, Docker, and Azure.
• Lead projects through all phases, from technical spikes/POCs to full production deployment.
• Green Field Innovation:
• Work on projects with vague or open-ended specifications, transforming abstract ideas into actionable, concrete components.
• Software Design Patterns:
• Implement and advocate for standard design patterns (eg, ports and adapters, provider patterns) to ensure system reliability and scalability.
• Data Source Integration:
• Interface with a variety of data sources including Postgres, Gremlin, and Neptune to build comprehensive and cohesive data solutions.

Required Skills & Experience

• Expertise in NLP:
• Proven experience in creating synthetic data, training classifiers, and deploying NLP models.
• Experience with fine-tuning and deploying LLMs.
• Familiarity with standard paradigms such as FTI (feature, training, and inference).
• Highly proficient working within the HuggingFace ecosystem
• Data Modeling Proficiency:
• Solid understanding and hands-on experience with semi-structured data models (RDF, RDFS) in a machine learning environment.
• Experience working with RDF based data sources ie JSON-LD, TTL, etc.
• Engineering Acumen:
• Strong software development skills with a track record of building and deploying applications using Python, Fast API, Docker, and Azure.
• Experience in taking projects from initial technical proof-of-concept to production-ready deployment.
• Adaptability & Innovation:
• Demonstrated ability to work in green field environments, converting vague requirements into practical solutions.
• Design Patterns Knowledge:
• Familiarity with standard design patterns (eg, ports and adapters, provider patterns) to architect scalable systems.
• Data Source Versatility:
• Proficient in handling a diverse range of data sources such as Postgres, Gremlin, and Neptune.

Preferred Skills

• Ontologies & Taxonomies:
• Knowledge of SKOS taxonomies and OWL ontologies.
• Experience applying NLP techniques in this context (eg, ontology embedding, text-to-SPARQL conversion).
• Vector Search & RAG Applications:
• Familiarity with vector search methodologies and developing Retrieval-Augmented Generation (RAG) applications, including reranking, embedding, and utilizing distributed platforms like Milvus and Qdrant.
• Advanced Visualisation:
• Experience with advanced data visualisation tools such as Plotly and Graphviz.

APPLY NOW!