326 to 350 of 419 Natural Language Processing Jobs in England

Scientist Manager, you will play a key part in leading a diverse global team of experts. We hire world-leading specialists in ML/NLP/GenAI, as well as Engineering, to drive the company’s leading internal AI model development. You will have the opportunity to publish your research … role if your background includes:*Required qualifications:** PhD in a relevant discipline.* 3+ years of hands-on experience leading teams building advanced ML/NLP/AI systems in academia (e.g. through student supervision) or industry.* Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL ...

long-term AI and discovery strategy across Elsevier platforms.Requirements: Master’s or PhD in Computer Science, Data Science, Machine Learning, Information Retrieval, Statistics, NLP, or a related quantitative field.Significant experience in Data Science, Machine Learning, Information Retrieval, Search Relevance, Evaluation Systems, or Applied AI.Significant experience leading and scaling high-performing … experience influencing senior leadership.Demonstrated ability to balance strategic leadership with pragmatic execution in rapidly evolving AI environments.Preferred qualificationsPhD preferred in Computer Science, Machine Learning, NLP, Information Retrieval, Statistics, or related field.Experience leading search, ranking, recommendation, or AI evaluation organizations at scale.Experience building evaluation systems for LLM-powered applications ...

long-term AI and discovery strategy across Elsevier platforms.**Requirements:*** Master’s or PhD in Computer Science, Data Science, Machine Learning, Information Retrieval, Statistics, NLP, or a related quantitative field.* 10+ years of experience in Data Science, Machine Learning, Information Retrieval, Search Relevance, Evaluation Systems, or Applied AI.* Significant experience … leadership.* Demonstrated ability to balance strategic leadership with pragmatic execution in rapidly evolving AI environments.**Preferred qualifications*** PhD preferred in Computer Science, Machine Learning, NLP, Information Retrieval, Statistics, or related field.* Experience leading search, ranking, recommendation, or AI evaluation organizations at scale.* Experience building evaluation systems for LLM-powered applications ...

technical capabilities of AI models Communicate strategy, initiatives, and progress transparently across the organisation Translate complex AI concepts, capabilities, and limitations into language that non‐technical stakeholders can act on Champion responsible AI practices: transparency in model outputs, bias monitoring, and compliance with client expectations around AI‐generated content … Experience in financial services, legal tech, or data/analytics platforms Familiarity with credit markets, debt instruments, or regulatory/compliance workflows Experience with NLP applied to document analysis (contracts, legal filings, financial reports) Experience with agent orchestration frameworks, tool use patterns, or multi‐step AI workflows Benefits Competitive, market ...

business needs and the technical capabilities of AI modelsCommunicate strategy, initiatives, and progress transparently across the organisationTranslate complex AI concepts, capabilities, and limitations into language that non-technical stakeholders can act onChampion responsible AI practices: transparency in model outputs, bias monitoring, and compliance with client expectations around AI-generated … newNice to HaveExperience in financial services, legal tech, or data/analytics platformsFamiliarity with credit markets, debt instruments, or regulatory/compliance workflowsExperience with NLP applied to document analysis (contracts, legal filings, financial reports)Experience with agent orchestration frameworks, tool use patterns, or multi-step AI workflowsBenefitsCompetitive, market-benchmarked salaryPension ...

research division of Thomson Reuters. We are focused on research and development, with a particular focus on advanced algorithms and training techniques for Large Language Models (LLMs). We are building a strong foundation of research capabilities across different areas and are looking for scientists who participate in designing … Research Scientist, you will play a key part in a diverse global team of experts. We hire world-leading specialists in ML/NLP/GenAI, as well as Engineering, to drive the company’s leading internal AI model development. You will have the opportunity to publish your research findings ...

research division of Thomson Reuters. We are focused on research and development, with a particular focus on advanced algorithms and training techniques for Large Language Models (LLMs). We are building a strong foundation of research capabilities across different areas and are looking for scientists who participate in designing … Research Scientist, you will play a key part in a diverse global team of experts. We hire world-leading specialists in ML/NLP/GenAI, as well as Engineering, to drive the company’s leading internal AI model development. You will have the opportunity to publish your research findings ...

build simulations and prototype data products.Experience validating quantitative findings with qualitative methods (e.g., surveys, user research).Demonstrated experience with applied AI, such as NLP, Large Language Models (LLMs), or Agentic AI for analytics.Deep experience in developing sophisticated customer segmentation models including predictive LTV modeling.Experience working within a two-sided ...

build simulations and prototype data products.Experience validating quantitative findings with qualitative methods (e.g., surveys, user research).Demonstrated experience with applied AI, such as NLP, Large Language Models (LLMs), or Agentic AI for analytics.Experience working within a two-sided marketplace, e-commerce, or the travel technology industry.Masters degree or equivalent ...

build simulations and prototype data products. Experience validating quantitative findings with qualitative methods (e.g., surveys, user research).Demonstrated experience with applied AI, such as NLP, Large Language Models (LLMs), or Agentic AI for analytics. Experience working within a two-sided marketplace, e-commerce, or the travel technology industry. Masters ...

Engineering was one of the earliest engineers at Figma. AI Engineer Responsibilities Build, experiment, and evaluate AI agents and ML models in the NLP domain to improve the accuracy of medical coding/billing and other aspects of revenue cycle management. Contribute to the building of internal AI frameworks … attitude. Clear communication skills Required 6+ years of ML/AI/data science in a production setting Well-versed in using ML/NLP python packages such as tensorflow, pytorch, scikit-learn, transformers (including others for working with huggingface models) Expertise in AI/ML and specifically in NLP ...

optimization of models to boost personalization, engagement, and traffic efficiency, balancing hands-on work with strategic leadership. The role requires advanced ML/NLP expertise, strong coding skills across Python/C++/Java, and collaboration with product, eng, and business teams. #J-18808-Ljbffr ...

BlackCube Labs in Durham, NC invites a Sr. Robotics Automation Architect to lead an enterprise transformation, bridging core RPA platforms, machine learning, and NLP-driven process discovery. This brand-new mandate targets 100+ automated workflows and scalable governance. You will design the technical architecture, drive implementation across UiPath Automation ...

real high-DoF hardware (humanoids, mobile manipulators, dual‐arm or legged platforms), including coordinating base and manipulator motion. Practical fluency with QP/NLP solvers and their failure modes: conditioning, infeasibility, warm starting, solve-time budgets, and what to do at the limit. Strong dynamic modelling foundations: rigid body kinematics ...

technologies and contribute to continuous innovation Essential Skills for the AI Engineer: Strong proficiency in Python with extensive experience using AI, ML and NLP libraries Hands-on experience working with modern large language models including prompt engineering, fine-tuning and evaluation Practical experience with core Generative AI frameworks ...

technical stakeholders Experience sharing knowledge with peers particularly the scientific/clinical domain. Nice to Have (Desirable Requirements) ML - Experience of classical ML and NLP methods Software craft – testing, observability, documentation, code review RAG pipelines at depth - experience building secure, compliant ingestion and retrieval systems with provenance tracking, including … automation, parsing, and document processing Agent frameworks - hands‐on experience with multi‐agent orchestration tools (e.g., Google ADK, StrandsAgents, LangGraph, CrewAI, or equivalents) Real world data sources – HER, claims, prescriptions, registries - and their pitfalls. AI-augmented development - effective use of agentic coding assistants (Copilot, Cursor, Claude Code) to accelerate ...

Computer Science, Data Science, Engineering, Informatics, or a related field.* Strong hands-on experience building and deploying AI/ML/DL/NLP/LLM systems in production environments.* Proficiency in Python and modern AI frameworks and tools (e.g. PyTorch, Transformers, Scikit-learn, OpenAI Codex, Claude Code).* Experience … Epic or Cerner).* Experience building commercial software products in regulated environments.* Publications or research experience in AI/ML/DL/NLP/LLM or biomedical informatics.* Startup or scale-up experience.## Perks and Benefits* Flexible working hours.* Benefits include private medical insurance, life insurance and travel cards. ...

like scaffolding, refactoring, debugging, test generation, and documentation Experience building or integrating AI/ML‐powered features into products or systems (e.g., recommendation engines, NLP models, computer vision, predictive analytics) Used context‐appropriate automated testing to inform software design choices and catch bugs Debugged and refactored pre‐existing code … Platform engineering: building reusable software foundations, internal developer platforms, and infrastructure that other teams build on Data Engineering: including platforms like Databricks for data processing and analytics Delivering production agentic systems, including RAG pipelines, vector search, and agentic frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, and n8n DevSecOps & DevOps ...

into actionable recommendations. Innovative Solutions: Combine structured datasets with unstructured sources (like text and customer interaction data) to create robust features and predictive models. NLP & GenAI Expertise: Apply traditional NLP techniques and cutting-edge GenAI tools for text classification, summarization, entity extraction, and more. Data Pipelines: Build, validate, and optimise … data science solutions that yield practical outcomes. Experience in combining structured and unstructured datasets for modelling and analysis. Strong background in NLP and GenAI techniques, including text classification, summarization, and embeddings. Advanced proficiency in SQL, Python, and PySpark, with a focus on software development best practises. Experience deploying data science ...

secure, intelligent solutions to complex business problems. Over 200,000 business customers and millions of individuals across 228 global markets today trust DeepL's Language AI platform for human-like translation, improved writing and real-time voice translation. Founded in 2017 by CEO Jaroslaw “Jarek” Kutylowski, DeepL … efficient training techniques. Experience fine‐tuning existing reasoning models for specific tasks and behaviours without degrading their reasoning capabilities. Experience with machine translation, multilingual NLP, or language quality estimation. Familiarity with inference and serving at scale (e.g. via vLLM, SGLang, TensorRT‐LLM, etc) and long‐context modelling. Publications ...

platforms. The role involves code development, deployment, and ongoing optimization to impact consumer experiences. The ideal candidate has solid experience in search technologies, NLP, and English proficiency, with a customer-focused approach and strong technical acumen. #J-18808-Ljbffr ...

PostgreSQL and S3. Build Event-Driven Architecture: Help move our architecture from scheduled pipelines towards real-time, event-driven services using messaging, queues, asynchronous processing and distributed systems. Build Infrastructure for AI Agents: Develop the infrastructure required to run increasingly agent-driven AI workflows … reliably in production, including state management, task execution, model routing, retries and observability. Support AI Infrastructure: Work closely with our AI engineers supporting production NLP, LLM and quantitative model workloads, including our in-house GPU infrastructure. Automate Infrastructure: Build and manage Infrastructure-as-Code using Pulumi and automate deployments through ...

agentic systems from prototype to production, with a strong understanding of infrastructure, authentication, and observability Delivered on high-stakes consulting engagements across multiple language paradigms, stacks, ecosystems, and client industries Built high-quality, maintainable software collaboratively, incrementally, and through an approach tailored towards the unique needs of the clients … embracing new tooling and trends within the software industry Built or integrated AI/ML features into products and systems, including recommendation engines, NLP, computer vision, predictive analytics, RAG pipelines, and agents Successfully led modernisation and replatforming efforts to align legacy systems with short and long-term business needs ...

innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team … following experience: Practical experience with Machine Learning problems, and a familiarity with Classical Machine Learning, Deep Learning and Statistical Modeling techniques Ph.D. in ML, NLP or a relevant field or MSc in CS, ML, Math, Statistics, Engineering, or related fields and previous relevant work experience Proficiency in software engineering ...

like scaffolding, refactoring, debugging, test generation, and documentation Experience building or integrating AI/ML‐powered features into products or systems (e.g., recommendation engines, NLP models, computer vision, predictive analytics) Used context‐appropriate automated testing to inform software design choices and catch bugs Debugged and refactored pre‐existing code … Strongly Preferred Skills MLOps: including tools like LangChain for application development and managing the ML lifecycle Data Engineering: including platforms like Databricks for data processing and analytics DevSecOps & DevOps Infrastructure as Code Building a truly diverse, equitable, and inclusive workplace is an ongoing journey, and we’re excited ...