14 of 14 Natural Language Processing Jobs in the North of England

Neo4J...) Data exchange and processing skills (e.g. ETL, ESB, API...) Development (e.g. Python) skills Big data technologies knowledge (e.g. Hadoop stack) Knowledge in NLP (Natural Language Processing) Knowledge in OCR (Object Character Recognition) Knowledge in Generative AI (Artificial Intelligence) would be advantageous Experience in containerisation technologies ...

grade data pipelines using Python, Scala, Spark, and SQL - Deep knowledge of AWS Cloud Platforms (EMR, Glue, Redshift, Kinesis, Lambda, DynamoDB) - Experience with data processing across structured and unstructured sources - Strong scripting abilities and API integration skills - Knowledge of data visualization and reporting best practices Desirable but not essential … Experience with data mining and machine learning - Natural language processing expertise - Multi-cloud platform experience They work within an Agile environment with Scrum practices, cross-functional collaborative teams and need someone who can work from the office 2 days a week. Salary: £50,000 - £95,000 + ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

with relevant projects An early-career technologist seeking formal qualifications and impactful work Essential skills: Strong foundation in AI/ML (e.g. neural networks, NLP, transformers) Proficiency in Python and ML frameworks (e.g. PyTorch, TensorFlow) Familiarity with LLM APIs and open-source models (e.g. GPT, Claude, Whisper) Understanding of agentic ...

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 ...

Staff Machine Learning Engineer - Fully Remote LLM & NLP required We are hiring for a Staff MLE to join a large global organisation delivering advanced language and AI solutions to clients. The Role Lead and architect large-scale machine learning projects Build and deploy scalable ML models, pipelines, and systems … understanding of ML algorithms, statistics, and data modelling Experience with large-scale data tools (Hadoop, Spark, Kafka) Cloud & MLOps experience (AWS, Azure, or GCP) NLP experience highly beneficial Strong leadership, communication, and stakeholder management ...

organisation is a forward-thinking technology business building data-driven products powered by advanced machine learning. They solve complex challenges across areas such as NLP, automation, and large-scale model deployment. With a distributed technical team across Europe, they emphasise collaboration, experimentation, and strong engineering standards. You'll join … engineers, championing best practices across coding, experimentation, and MLOps. Collaborate with Product and Engineering teams to define priorities and model strategy. Apply deep learning, NLP or classical ML techniques to real-world, high-impact problems. Uphold responsible AI principles across model development and evaluation. YOUR SKILLS & EXPERIENCE The successful Staff ...

standards and tooling-RDF/RDFS, SPARQL, OWL, SHACL-together with graph databases, ontology-design tools, and visualization platforms such as Linkurious. Apply modern NLP/NLU techniques, from topic modelling to cutting edge entity and relation extraction, plus concise text summarisation. Experience Requirements: Core semantic/graph tech …/streaming or CDC pipelines feeding a knowledge graph. Entity resolution techniques, data cleansing, enrichment, and integration from many sources. Python + ML/NLP stack High quality production code in Python . Libraries such as NetworkX , TensorFlow or PyTorch , NLTK, spaCy, Hugging Face, BERT , Pandas, NumPy, scikit learn . ...