5 of 5 Permanent Natural Language Processing Jobs in Newcastle upon Tyne

Machine Learning Research Engineer - NLP/LLM An incredible opportunity for a Machine Learning Research Engineer to work on researching and investigating new concepts for an industry-leading, machine-learning software company in Cambridge, UK. This unique opportunity is ideally suited to those with a Ph.D. relating to classic Machine … leading University in a Computer Science, Physics, Maths or similar (we are very keen to hear from those with a Ph.D. directly related to NLP) Experience weighted more towards classic machine learning than AI Engineering Strong knowledge in LLMs, NLP and Machine Learning/AI Excellent academics throughout including ...

track record running Agile PoCs and MVPs and scaling them into production within complex organizations. Strong understanding of AI/ML techniques (e.g., classification, NLP, GenAI, RAG, prompt engineering), data pipelines, APIs, and microservices. Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also valued) and MLOps tools ...

results to stakeholders and executives effectively. Overlap of 6 hours with PST time zone is mandatory. Required Skills & Qualifications: Strong background in Machine Learning, NLP, and modern deep learning architectures (Transformers, LLMs). Hands-on experience with frameworks such as PyTorch, TensorFlow, Hugging Face, or DeepSpeed Hands-on experience ...

sources (streaming, batch, cloud, on-premises) using Azure, AWS, and GCP services. AI & ML Leadership Architect advanced Data Science, ML and AI solutions, including NLP, RAG LLM and Agentic AI systems. Oversee the implementation of MLOps frameworks, ensuring robust deployment, monitoring, and lifecycle management of ML models. Evaluate and recommend ...

Responsibilities Design and implement robust data pipelines and ML workflows using Python, SQL, Spark, and Databricks. Develop and deploy machine learning models (including NLP, deep learning, and agentic AI) in production environments. Integrate data from diverse sources, including streaming and batch ingestion, using Azure Data Factory, GCP Dataflow ...