176 to 200 of 419 Natural Language Processing Jobs in England

other processing of unstructured content. Most use cases are creative chains of multiple steps drawn from data processing, exploratory analysis, fundamental ML, NLP, SQL, LLMs and integration into our live systems. What you’ll do Lead the team Manage, coach and develop Penta’s Data Science team, setting … execution, quality, pace, maintainability and cost discipline. Ship production data science and AI systems Design, build and review data science solutions across NLP, LLM workflows, machine learning, SQL and large‐scale content processing. Own technical design and architecture for data‐science‐enabled applications, ensuring solutions are maintainable, supportable, observable ...

validation of Agentic AI-driven product capabilities within Protégé in PatentSight. This role focuses on defining what to build and why, leveraging machine learning, NLP, and large language models (LLMs) to solve complex Intellectual Property (IP) workflows. You will help drive experimentation, modeling, and evaluation, partnering closely with engineers … translate validated approaches into scalable, customer-facing solutions.Key Responsibilities:Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies, patent search).Define agentic workflows and reasoning strategies for multi-step IP tasks.Develop retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality ...

validation of Agentic AI-driven product capabilities within Protégé in PatentSight. This role focuses on defining what to build and why, leveraging machine learning, NLP, and large language models (LLMs) to solve complex Intellectual Property (IP) workflows. You will help drive experimentation, modeling, and evaluation, partnering closely with engineers … translate validated approaches into scalable, customer-facing solutions. Key Responsibilities: Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies, patent search). Define agentic workflows and reasoning strategies for multi-step IP tasks. Develop retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g. ...

validation of Agentic AI-driven product capabilities within Protégé in PatentSight. This role focuses on defining what to build and why, leveraging machine learning, NLP, and large language models (LLMs) to solve complex Intellectual Property (IP) workflows. You will help drive experimentation, modeling, and evaluation, partnering closely with engineers … translate validated approaches into scalable, customer-facing solutions. **Key Responsibilities:*** Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies, patent search).* Define agentic workflows and reasoning strategies for multi-step IP tasks.* Develop retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g. ...

validation of Agentic AI-driven product capabilities within Protégé in PatentSight. This role focuses on defining what to build and why, leveraging machine learning, NLP, and large language models (LLMs) to solve complex Intellectual Property (IP) workflows. You will help drive experimentation, modeling, and evaluation, partnering closely with engineers … translate validated approaches into scalable, customer-facing solutions. Key Responsibilities: Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies, patent search). Define agentic workflows and reasoning strategies for multi-step IP tasks. Develop retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g. ...

3+ years of experience in backend software development, building scalable, resilient, and production-grade systems Hands-on experience developing AI-powered applications, including large language models (LLMs), AI agents, retrieval-augmented generation, prompt engineering, evaluation frameworks, and model optimization techniques Proven ability to take AI solutions from concept … world production environments. Working at the intersection of software engineering and machine learning, you will design and develop systems that power AI agents, large language model applications, and advanced automation solutions used by teams across the business. You will collaborate closely with engineers, data scientists, and product partners ...

Competencies3+ years of experience in backend software development, building scalable, resilient, and production-grade systemsHands-on experience developing AI-powered applications, including large language models (LLMs), AI agents, retrieval-augmented generation, prompt engineering, evaluation frameworks, and model optimization techniquesProven ability to take AI solutions from concept and experimentation through … learningAbout the TeamOur Innovation team is responsible for building next-generation internal and external products powered by cutting-edge artificial intelligence technologies, including large language models, AI agents, machine learning, and natural language processing.The group is made up of a diverse set of engineers, data scientists ...

with clients to solve their most complex challenges. Design and implement end-to-end ML pipelines from experimentation to production Lead model development across NLP, computer vision, and time‐series forecasting Architect scalable model serving infrastructure on cloud platforms (AWS/GCP/Azure) Conduct rigorous model evaluation, A/ ...

with the ability to personally contribute high-quality production code while guiding technical direction Deep hands‐on expertise building enterprise AI applications using large language models, AI agents, retrieval‐augmented generation, prompt engineering, orchestration frameworks, evaluation methods, and model optimisation techniques Proven ability to take complex AI solutions from … application programming interfaces, data pipelines, inference pipelines, and platform capabilities that support real‐time and batch AI workloads at enterprise scale Implement advanced large language model applications using retrieval‐augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration Make key technical decisions while remaining accountable ...

similar, with the ability to personally contribute high-quality production code while guiding technical directionDeep hands-on expertise building enterprise AI applications using large language models, AI agents, retrieval-augmented generation, prompt engineering, orchestration frameworks, evaluation methods, and model optimisation techniquesProven ability to take complex AI solutions from prototype … services, application programming interfaces, data pipelines, inference pipelines, and platform capabilities that support real-time and batch AI workloads at enterprise scaleImplement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integrationMake key technical decisions while remaining accountable ...

with the ability to personally contribute high-quality production code while guiding technical direction - Deep hands-on expertise building enterprise AI applications using large language models, AI agents, retrieval-augmented generation, prompt engineering, orchestration frameworks, evaluation methods, and model optimisation techniques - Proven ability to take complex AI solutions from … application programming interfaces, data pipelines, inference pipelines, and platform capabilities that support real-time and batch AI workloads at enterprise scale - Implement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration - Make key technical decisions while remaining accountable ...

with the ability to personally contribute high-quality production code while guiding technical direction - Deep hands-on expertise building enterprise AI applications using large language models, AI agents, retrieval-augmented generation, prompt engineering, orchestration frameworks, evaluation methods, and model optimisation techniques - Proven ability to take complex AI solutions from … application programming interfaces, data pipelines, inference pipelines, and platform capabilities that support real-time and batch AI workloads at enterprise scale - Implement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration - Make key technical decisions while remaining accountable ...

experience with frameworks such as PyTorch, TensorFlow, and Hugging Face.Experience taking AI proof-of-concepts from idea to production.Strong knowledge of deep learning, NLP, and LLM architectures and experience in fine-tuning LLMs or training domain-specific models, RAG, embeddings, and vector databases.Familiarity with agentic AI concepts and orchestration frameworks.Experience ...

with frameworks such as PyTorch, TensorFlow, and Hugging Face. Experience taking AI proof-of-concepts from idea to production. Strong knowledge of deep learning, NLP, and LLM architectures and experience in fine-tuning LLMs or training domain-specific models, RAG, embeddings, and vector databases. Familiarity with agentic AI concepts ...

business value.Bonus Points ForParticipation in Kaggle or other data science competitions.Experience with MLOps practices (CI/CD, model monitoring, DevOps integration).Familiarity with advanced NLP frameworks such as spaCy or Transformers and exposure to AI technologies including Generative AI or LLMs.MSc or PhD in a numerate discipline.Financial services or banking ...

Bonus Points ForParticipation in Kaggle or other data science competitions. Experience with MLOps practices (CI/CD, model monitoring, DevOps integration).Familiarity with advanced NLP frameworks such as spaCy or Transformers and exposure to AI technologies including Generative AI or LLMs. MSc or PhD in a numerate discipline. Financial services ...

cloud platforms (AWS, Azure, or GCP) Experience of containerisation (Docker) and orchestration (Kubernetes) Exposure to data engineering tools/libraries (e.g. Pandas, NumPy) or NLP libraries Knowledge of message queues/event-driven architecture (e.g. RabbitMQ, Kafka) Understanding of CI/CD tools (e.g. Jenkins, GitHub Actions, Azure DevOps) Experience ...

solving mindset with the ability to operate independently and step up into a leadership vacuum when needed.What we prefer you have:Experience with advanced NLP techniques beyond prompt engineering, including fine-tuning and evaluation frameworks for generative models. Experience working in the (re)insurance industry, with an understanding of underwriting ...

mindset with the ability to operate independently and step up into a leadership vacuum when needed. What we prefer you have: Experience with advanced NLP techniques beyond prompt engineering, including fine‐tuning and evaluation frameworks for generative models. Experience working in the (re)insurance industry, with an understanding of underwriting ...

Experience designing, testing and deploying production-scale AI/ML solutions (APIs, microservices, cloud deployment, endpoint deployment, registries, pipelines)Experience with LLM based applications (NLP, embeddings, semantic search, RAG, Graph RAG, fine-tuning)Proficient in ML tools and modern ecosystem (PyTorch, MLFlow, FastAPI, SQL Alchemy)Experience retrieving data from structured ...

with datasets, ETL pipelines, and metrics definition Nice to have (but not essential) Experience with agentic workflow systems and complex orchestration patterns Background in NLP or contributions to open‐source AI/ML projects Experience with model fine‐tuning or custom training approaches Familiarity with MLOps platforms and experiment tracking ...

machine learning models, from problem framing and experimentation through to live deployment and monitoring. Technical depth: Apply strong statistical modelling, ML, and (where relevant) NLP/LLM techniques to solve real business problems, not just exploratory analysis. Experimentation and measurement: Design and run experiments (A/B testing, causal inference ...

analytical and problem-solving skills Excellent communication and teamwork abilities Genuine passion for AI and emerging technologies Desirable Skills Exposure to Generative AI, LLMs, NLP, or computer vision projects Knowledge of AWS, Azure, or GCP Familiarity with Docker, APIs, or Git workflowsFamiliarity with frameworks such as PyTorch, TensorFlow, or Scikit ...

machine learning models, from problem framing and experimentation through to live deployment and monitoring. Technical depth: Apply strong statistical modelling, ML, and (where relevant) NLP/LLM techniques to solve real business problems, not just exploratory analysis. Experimentation and measurement: Design and run experiments (A/B testing, causal inference ...

including working with datasets, ETL pipelines, and metrics definitionNice to have (but not essential)Experience with agentic workflow systems and complex orchestration patternsBackground in NLP or contributions to open-source AI/ML projectsExperience with model fine-tuning or custom training approachesFamiliarity with MLOps platforms and experiment tracking toolsExperience with ...