51 to 75 of 412 Natural Language Processing Jobs in the UK

recruit a Data Scientist with 7 to 10 years expertise as a Data Scientist. You will have Natural Language Processing (NLP) knowledge and experience and understand and analyse large data sets to discover new insights. Working in a multi-disciplinary team within a highly technical and complex ...

Data Expert with 7 to 10 years expertise as a Big Data Scientist. You will have Natural Language Processing (NLP) knowledge and experience and understand and analyse large data sets to discover new insights. Working in a multi-disciplinary team within a highly technical and complex environment. ...

software for the life sciences industry, offering the only fully cloud-based, 100% configurable and flexible solutions utilizing natural language processing (NLP) to accelerate clinical trials. 4G Clinical is headquartered in the Boston Biotech corridor of Wellesley, MA, with offices in Europe and Asia. We offer compelling ...

Engineer with a strong quantitative background to work on real‐world prediction problems within financial markets. The role combines statistical modelling, machine learning research, natural language processing, and large language model applications in a production investment environment. You will develop predictive models across fixed income … Large language models. Retrieval‐augmented generation. Document understanding systems. Information extraction. Long‐context document processing. Prompt engineering. Structured generation techniques. Evaluation framework design. NLP pipelines. Text analytics. Programming and Engineering Python. SQL. Git or equivalent version‐control systems. Software engineering best practices. Data pipeline development. Production machine learning systems. ...

software for the life sciences industry, offering the only fully cloud-based, 100% configurable and flexible solutions utilizing natural language processing (NLP) to accelerate clinical trials. 4G Clinical is headquartered in the Boston Biotech corridor of Wellesley, MA, with offices in Europe and Asia. We offer compelling ...

Responsibilities Responsible for NLP research and development including LLM reasoning, conversational agents, machine translation, part-of-speech tagging, sentence analysis and named entity recognition. Optimize existing online algorithms, develop efficient and reliable NLP solutions by combining business needs and data. Explore applications of NLP techniques and deep learning algorithms … games. Follow the latest developments in academia and industry and quickly apply findings in your work. Qualifications Familiar with NLP fundamentals, with a strong understanding of statistical models, related machine learning principles, and experience working on NLP related projects. Proficient in at least one programming language, familiar with basic ...

NLP/LLM Scientist - Applied AI ML Lead - Machine Learning Centre of Excellence The Machine Learning Center of Excellence invites the successful candidate to apply sophisticated machine learning methods to a wide variety of complex tasks including natural language processing, large language models, and recommendation systems. … knowledge sharing community Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as NLP, LLMs or recommendation systems Produce outputs that lead to high-impact business applications, open-source software, patents, and publications in top AI/ML conferences ...

test splits, with clear lineage from raw data to model input. Eval harness: build an automated harness that benchmarks vision-language and NLP models against clinically meaningful metrics, tracks regressions and supports build-vs-buy model decisions. 2. Clinical knowledge base Build the structured clinical knowledge base that turns … models. Experience running data labelling and training-data preparation, including annotation tooling and quality control. Working knowledge of databases and data modelling. Practical NLP experience: entity extraction, entity linking or document parsing. Comfort handling sensitive data under data protection and clinical safety constraints. Pragmatism and speed: you can work ...

frameworks such as LangChain, LangGraph, Auto-GPT Deep knowledge and experience in machine learning and artificial intelligence Expertise in at least one area: Large Language Models, Natural Language Processing, Knowledge Graph, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis Knowledge ...

into a team. You will own the entire model stack: building custom deep-learning models and training and fine-tuning our own large language models to outperform off-the-shelf commercial models on our mission, using a proprietary dataset at a scale most labs never see. You will shape … research direction alongside the founder, raise the bar, and build the team you lead. Responsibilities Lead research and development efforts focused on large language models to advance Kangal AI's product offerings. Design and implement novel algorithms and architectures tailored to improve LLM performance and applicability. Collaborate with interdisciplinary ...

frameworks such as LangChain, LangGraph, Auto-GPT Deep knowledge and experience in machine learning and artificial intelligence Expertise in at least one area: Large Language Models, Natural Language Processing, Knowledge Graph, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis Knowledge ...

Scope We are seeking an Engineering Manager to lead our Applied AI and Data Science team: a multidisciplinary group of AI Engineers, ML Engineers, NLP Engineers and Data Scientists. This is a player-coach role. You will own the health, delivery and growth of the team while remaining a hands … stepping into implementation when it matters. The team’s work spans generative and agentic AI systems built on large language models, alongside the NLP and predictive models that sit behind our products and internal tools. You will turn the Group’s AI ambitions into well-architected, production-grade systems ...

ML. Strong preference for candidates that have worked directly in building foundation models. In-depth knowledge of machine learning, particularly when it comes to Natural Language Processing & Large Language Models (LLMs). Bonus points for experience with Multimodal AI. Experience with working in a chaotic, fast ...

translation guidelines for human annotators. Use Python, pandas and SQL to analyse datasets and support research workflows. Work directly with research scientists, ML/NLP engineers and data scientists , translating complex linguistic findings into actionable insights. Evaluate linguistic vendor outputs, identify error patterns and provide actionable quality feedback. Linguist … Dravidian or Bantu language ; Swahili is particularly valuable . Other low-resource language expertise is highly regarded. Linguist IC3 Experience applying basic NLP techniques and ideally collaborating with ML, NLP, software engineering or data-science teams. Strong research and business communication skills, with the ability to explain linguistic ...

robust ML and data pipelines for experimentation and deployment. Design, build, and optimize risk models for analytics and generative AI applications using our proprietary NLP data generation process. Collaborate cross functionally with Economists, Industry Analysts, Political Scientists, and Developers. Explain ML/NLP model outputs and methodologies to non-technical … Substantial experience with Python, R, and relevant libraries (e.g., numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot, etc.). Proven experience developing, refining, and monitoring NLP models. Familiarity with database management tools and techniques (e.g., SQL, Selenium, S3, Sagemaker, API protocols) is preferred but not required. Understanding model evaluation methods ...

robust ML and data pipelines for experimentation and deployment. Design, build, and optimize risk models for analytics and generative AI applications using our proprietary NLP data generation process. Collaborate cross functionally with Economists, Industry Analysts, Political Scientists, and Developers. Explain ML/NLP model outputs and methodologies to non-technical … Substantial experience with Python, R, and relevant libraries (e.g., numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot, etc.). Proven experience developing, refining, and monitoring NLP models. Familiarity with database management tools and techniques (e.g., SQL, Selenium, S3, Sagemaker, API protocols) is preferred but not required. Understanding model evaluation methods ...

Advanced Python and software engineering. You write clean, production‐grade code rather than scripts, with a good working knowledge of object‐oriented design, asynchronous processing, packaging and automated testing. Generative AI and agentic development. Practical experience with prompt engineering, retrieval‐augmented generation pipelines, context management, embeddings and vector databases … fluency in English working in global, cross‐functional teams. Preferred: Experience applying AI to customer, marketing, commerce, sales or service challenges. Experience with natural language processing, computer vision or multimodal AI models. Knowledge of Responsible AI, guardrails and safety practices in production environments. Familiarity with Snowflake, Databricks ...

role could involve working across a broad range of technologies and engineering disciplines, including: Artificial Intelligence and machine learning AI systems engineering and integration Natural Language Processing Computer vision and image processing Quantum technologies C++ and Python development Modern web technologies Cloud-native engineering Distributed systems ...

/ML frameworks—TensorFlow, PyTorch, Scikit‐Learn, Transformers—cloud platforms (AWS, Azure, GCP), and modern software engineering practices. Strong background in deep learning, natural language processing, computer vision, or reinforcement learning. Engineering Excellence: Proven experience building production‐scale AI systems with focus on performance, reliability, and maintainability. ...

fundamentals of statistics, optimization and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, autoencoders etc.) Specialism or well-researched interest in NLP Broad knowledge of MLOps tooling – for versioning, reproducibility, observability etc. Experience monitoring, maintaining, enhancing existing models over an extended time period Extensive experience with pytorch … streaming microservices exposed as REST/gRPC endpoints Experience with container orchestration tools (e.g. Kubernetes, Helm) Knowledge of open source datasets and benchmarks in NLP Hands‐on experience in implementing distributed/multi‐threaded/scalable applications Track record of developing, deploying business critical machine learning models #J-18808-Ljbffr ...

planning sensible modernisation and retirement pathways. Data science, AI and intelligent automation Identify high‐value use cases for machine learning, generative AI, computer vision, natural language processing, optimisation and robotic process automation. Lead the design, validation, deployment and monitoring of models such as propensity, customer segmentation, forecasting …/GitHub, CI/CD, VB/VBA, C#, HTML, CSS, JavaScript and full‐stack patterns Data science and AI-Forecasting, classification, clustering, recommendation, NLP, LLMs, RAG, embeddings, vector databases, OCR, computer vision and model monitoring Automation-Workflow automation, RPA, API integration and human‐in‐the‐loop process design Person ...

maintainable, production‐ready and can be readily adapted to future developments. Choose the right approach for the problem at hand, evaluating classical ML and NLP techniques, LLM‐based solutions, and agentic solutions to balance trade‐offs between speed, cost, complexity, interpretability, and performance. Collaborate closely with product, design, and other … frameworks such as PyTorch, TensorFlow, or LangChain, with experience packaging models into APIs or integrating them into applications. A solid understanding of LLMs for natural language processing applications, including topics such as embeddings, prompt engineering and fine‐tuning. Strong software engineering foundations such as version control, unit ...

maintainable, production‐ready and can be readily adapted to future developments. Choose the right approach for the problem at hand, evaluating classical ML and NLP techniques, LLM‐based solutions, and agentic solutions to balance trade‐offs between speed, cost, complexity, interpretability, and performance. Collaborate closely with product, design, and other … frameworks such as PyTorch, TensorFlow, or LangChain, with experience packaging models into APIs or integrating them into applications. A solid understanding of LLMs for natural language processing applications, including topics such as embeddings, prompt engineering and fine‐tuning. Strong software engineering foundations such as version control, unit ...

sensitive data (e.g., Personally Identifiable Information). Strong knowledge of a programming languages for data science (Python, R, etc.) including best practices using this language to write robust software. An understanding of data governance and best practices to ensure data protection. Experience planning technical activities and structuring work … bachelor’s degree in a STEM field. Desirable skills and experience Experience working in a professional services/consultancy environment preferred. Experience solving natural language processing problems. Experience creating generative AI applications, such as chatbots or RAG retrieval systems. Stay up to date with cutting edge ...

tools such as calendars, task managers, and communication apps. Create architectural blueprints for new AI features and services, considering factors such as data flow, processing requirements, and user experience. Establish best practices, coding standards, and architectural guidelines for the development team. Evaluate and recommend new technologies, frameworks, and tools …/ML systems). Proven track record of designing and implementing large‐scale, distributed AI systems. Deep understanding of AI and machine learning (natural language processing, computer vision, predictive modeling). Extensive experience with cloud platforms (AWS, Google Cloud, Azure) and their AI/ML offerings. Strong ...