26 to 50 of 69 Natural Language Processing Jobs in the UK excluding London

stakeholders to understand business challenges and translate them into actionable AI strategies. Key responsibilities: Collaborating with clients to identify opportunities for AI implementation Designing and developing AI models (ML, NLP, Computer Vision) Conducting data analysis and preprocessing Deploying models into production environments Providing training and support on AI tools and best practices Staying up to date with the latest AI More ❯

stakeholders to understand business challenges and translate them into actionable AI strategies. Key responsibilities: Collaborating with clients to identify opportunities for AI implementation Designing and developing AI models (ML, NLP, Computer Vision) Conducting data analysis and preprocessing Deploying models into production environments Providing training and support on AI tools and best practices Staying up to date with the latest AI More ❯

stakeholders to understand business challenges and translate them into actionable AI strategies. Key responsibilities: Collaborating with clients to identify opportunities for AI implementation Designing and developing AI models (ML, NLP, Computer Vision) Conducting data analysis and preprocessing Deploying models into production environments Providing training and support on AI tools and best practices Staying up to date with the latest AI More ❯

stakeholders to understand business challenges and translate them into actionable AI strategies. Key responsibilities: Collaborating with clients to identify opportunities for AI implementation Designing and developing AI models (ML, NLP, Computer Vision) Conducting data analysis and preprocessing Deploying models into production environments Providing training and support on AI tools and best practices Staying up to date with the latest AI More ❯

stakeholders to understand business challenges and translate them into actionable AI strategies. Key responsibilities: Collaborating with clients to identify opportunities for AI implementation Designing and developing AI models (ML, NLP, Computer Vision) Conducting data analysis and preprocessing Deploying models into production environments Providing training and support on AI tools and best practices Staying up to date with the latest AI More ❯

stakeholders to understand business challenges and translate them into actionable AI strategies. Key responsibilities: Collaborating with clients to identify opportunities for AI implementation Designing and developing AI models (ML, NLP, Computer Vision) Conducting data analysis and preprocessing Deploying models into production environments Providing training and support on AI tools and best practices Staying up to date with the latest AI More ❯

stakeholders to understand business challenges and translate them into actionable AI strategies. Key responsibilities: Collaborating with clients to identify opportunities for AI implementation Designing and developing AI models (ML, NLP, Computer Vision) Conducting data analysis and preprocessing Deploying models into production environments Providing training and support on AI tools and best practices Staying up to date with the latest AI More ❯

stakeholders to understand business challenges and translate them into actionable AI strategies. Key responsibilities: Collaborating with clients to identify opportunities for AI implementation Designing and developing AI models (ML, NLP, Computer Vision) Conducting data analysis and preprocessing Deploying models into production environments Providing training and support on AI tools and best practices Staying up to date with the latest AI More ❯

taught AI/ML practitioner 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 AI frameworks (e.g. LangChain, AutoGen More ❯

combining deep technical expertise with strategic client engagement. As a Solutions AI Architect, you will: Lead the design and delivery of AI and cloud-native architectures, including Generative AI, NLP, and LLM solutions. Act as a trusted advisor to senior stakeholders, guiding AI roadmaps and strategy. Translate complex business needs into scalable AI-driven solutions across public cloud, edge, and More ❯

Computer Science, Business, or equivalent experience. 5+ years of professional experience (for senior roles, 7+), ideally in IT support, product operations, or digital assistant environments. Familiarity with Generative AI, NLP, or LLM-based technologies (e.g., ChatGPT, Azure OpenAI). Strong written and verbal communication skills across technical and non-technical audiences. Experience improving support processes and documentation at scale. Analytical More ❯

engineers, translating insights into actionable recommendations, and ensuring data science practices align with organisational goals. Key Responsibilities Customer Insights: Build churn prediction models, apply clustering and segmentation, and use NLP for sentiment analysis to improve service quality and retention strategies. Operational Performance: Develop forecasting models for network demand, implement anomaly detection for outages and latency, and create predictive maintenance solutions More ❯

not only technically skilled in Python and machine learning but also eager to explore, learn, and build secure, scalable AI solutions. Responsibilities Building, integrating, testing and scaling models including NLP and Computer Vision. Take ownership of developing, training and productionising machine learning lifecycles, adhering to best practices, security needs and quality assurance. Developing deep learning architectures and implementing neural networks More ❯

modern cloud and AI technologies. Key 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 and AWS services. Apply data modelling More ❯

Efficiency in ideation and implementation, prioritizing tasks based on urgency and impact. Experience with Docker and containerized deployments. Proficiency in deploying high availability applications on Kubernetes. Preferred: Experience deploying NLP or TTS models to production. What We Offer A dynamic environment where your contributions shape the company and its products. A team that values innovation, intuition, and drive. Autonomy, fostering More ❯

Efficiency in ideation and implementation, prioritizing tasks based on urgency and impact. Experience with Docker and containerized deployments. Proficiency in deploying high availability applications on Kubernetes. Preferred: Experience deploying NLP or TTS models to production. What We Offer A dynamic environment where your contributions shape the company and its products. A team that values innovation, intuition, and drive. Autonomy, fostering More ❯

Expertise: Solid understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning). Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we have built, and we welcome applications from More ❯

document schemas, metadata, hybrid/dense retrieval, re-ranking, and grounding. Manage vector/keyword indexes (e.g., Azure AI Search , pgvector, Pinecone/Weaviate). Develop and deploy advanced NLP, information retrieval, and recommendation systems that enhance Chambers and Partners’ research and product offerings, including document understanding, automatic summarisation, topic modelling, semantic search, entity recognition, and relationship extraction. Design and More ❯

structures for describing regulation to create a regulatory commons. Our team benefits from a strong connection to the University, bringing together deep expertise in scaling tech start-ups, developing NLP/ML models, and collaborating with regulatory communities. Backed by £15 million in funding, we have established a solid product-market fit and are experiencing significant commercial traction with global More ❯

teams on effective AI adoption and usage. Contribute to the development of scalable prototypes and production-ready solutions. Ideal Candidate Hands-on experience with AI/ML tools (e.g. NLP, predictive modelling, process automation). Familiarity with cloud platforms (AWS, Azure, or GCP). LLM experience Strong problem-solving and collaboration skills. Ability to communicate technical concepts clearly to non More ❯

of commercial experience in a Data Science role building statistical & machine learning models. Have built and deployed machine learning models in production. Excellent use of Python Particular experience in NLP, LLMs, and RAGs are highly prized given the focus on these projects. CI/CD & MLOps experience is valued Databricks experience is valued If this role interests you and you More ❯

firm Advanced degree (PhD or Master's) in Computer Science, Mathematics, Physics, Engineering, or related discipline Strong expertise in modern ML techniques: time-series forecasting, deep learning, ensemble methods, NLP, or RL Expert-level programming skills in Python and strong understanding of software engineering best practices Experience deploying ML models to production in real-time or high-frequency environments Deep More ❯

understanding of Git/GitHub workflows and DevOps tooling Nice to have: Experience with Docker or multi-container application architecture Familiarity with AI/ML technologies such as LLMs, NLP, LangGraph, PydanticAI, or AutoGen Experience with biological or scientific datasets (genomics, proteomics, etc.) Exposure to frontend development (React preferred) Experience benchmarking and improving AI/ML models or agent-based More ❯

understanding of Git/GitHub workflows and DevOps tooling Nice to have: Experience with Docker or multi-container application architecture Familiarity with AI/ML technologies such as LLMs, NLP, LangGraph, PydanticAI, or AutoGen Experience with biological or scientific datasets (genomics, proteomics, etc.) Exposure to frontend development (React preferred) Experience benchmarking and improving AI/ML models or agent-based More ❯

data, or automation-driven projects within financial services or another highly regulated environment. Strong understanding of technology-enabled change, particularly involving data platforms, analytics, or automation tools (e.g. ML, NLP, RPA, GenAI). Excellent stakeholder management and communication skills, with the ability to influence at senior and executive levels. Strong project planning, governance, and risk management skills across both Agile More ❯