26 to 50 of 269 Natural Language Processing Jobs in London

Braunford LLP is seeking a Natural Language Processing (NLP) Researcher to tackle complex quantitative finance problems from our London HQ. You will work with large text corpora and use state-of-the-art NLP techniques to predict future market behavior. The role requires expertise in NLP, machine ...

customer service, supply chain optimization, recommendation systems, and internal operations. Develop robust agent architectures, incorporating machine learning models, natural language processing (NLP), knowledge representation, and reasoning techniques. Integrate AI agents with existing JD.com systems and platforms, ensuring seamless functionality and data flow. Conduct research and experimentation with … proficiency in programming languages such as Python, Java, or C++. In-depth understanding of machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and NLP techniques. Experience with agent-based modeling, reinforcement learning, multi-agent systems, or cognitive architectures. Solid understanding of software engineering principles, including design patterns, data structures ...

sound architecture decisions. Demonstrated experience with AI/ML technologies, including LLMs, Retrieval Augmented Generation (RAG), agentic workflows, Natural Language Processing (NLP), and predictive analytics, and the discipline to run them reliably in production. Track record of building on shared enterprise data platforms (for example Snowflake ...

client focus. Ability to work in agile cross-functional teams. Preferred Qualifications, Capabilities, and Skills Experience with Natural Language Processing (NLP). Ability to design intrinsic and extrinsic evaluations of a model's performance aligned with business goals. Ability to work with non-specialists in a partnership ...

delivery of new SOTA challenger models Tuning and optimising strategies for incumbent models Design and govern the use of Large Language Models (LLM)-as-judge approaches within alert handling processes (evaluation framework, quality controls, bias/robustness testing and auditability) Document model logic, assumptions, limitations and test outcomes … experience developing analytical or machine learning models in financial services (ideally Anti-Financial Crime/Screening) Experience building Natural Language Processing (NLP)/Machine Learning (ML)/Artificial Intelligence (AI) pipelines, including feature engineering, model training, evaluation and monitoring Experience with hyperparameter tuning at scale and experimentation ...

particularly in relation to demand and supply forecasting. Bonus: Experience in the energy or utilities industry. Exposure to Natural Language Processing (NLP) or other related fields. Familiarity with data engineering practices and working with large datasets. Competitive salary and a stock options sign-on bonus Biannual bonus ...

responsibilitiesDeveloping advanced analytical models using consumer and market datasets to identify emerging risks, trends and consumer harm signals while applying statistical, machine learning and natural language processing techniques to extract insights from structured and unstructured dataDesigning, testing and deploying scalable analytical solutions that improve the efficiency, consistency … both technical and non-technical stakeholders, enabling data-driven decisionsEssential:Solid knowledge of data science methodologies, including statistical modelling, predictive analytics, machine learning and natural language processingExperience developing scalable analytical solutions and designing repeatable workflows focused on automation, efficiency and reproducibilityProficient Python programming skills, with experience using analytical ...

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. ...

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 ...

/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 ...

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 ...

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 ...