1 to 25 of 58 Permanent Natural Language Processing Jobs in London

rapidly react to trader/sales/management demands in traditional ways but also using techniques in natural language processing (NLP) and machine learning (ML) and artificial intelligence (AI) to maximize our return on the large-scale data sets we curate. What we’ll offer … Experience working with data, both in onboarding, cleaning and curating data in databases as well as analysis and presentation First degree in Maths/Natural Science/Computer Science/Engineering, PhD or Masters desirable. Some experience of machine learning and natural language processing a bonus ...

requires rapidly reacting to trader/sales/management demands in traditional ways but also using techniques in natural language processing (NLP) and machine learning (ML) and artificial intelligence (AI) to maximize our return on the large-scale data sets we curate. What we’ll offer … tools in a collaborative environment (git/bitbucket/JIRA etc.) Advanced Degree (PhD OR Masters) in a relevant subject such as Mathematics/Natural Science/Computer Science/Engineering Experience working with data, both in onboarding, cleaning and curating data in databases as well as analysis ...

primary Tungsten Automation solutions and offerings AI and ML Capabilities : Leverage AI and machine learning capabilities, including natural language processing (NLP), computer vision, and LLMs, to optimize document processing, data extraction, and decision-making workflows Programming and Development : Apply relevant programming skills (e.g., Python, Java … related field, with a focus on enterprise-scale implementations Deep AI expertise with technical understanding of AI/GAI technologies, including LLMs, machine learning, NLP, and computer vision, and their application in business automation Platform knowledge with strong technical knowledge of the TotalAgility platform or similar intelligent automation platforms Integration ...

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 designing evaluation frameworks for LLM use cases ...

patterns, and anomalies across diverse datasets. Develop and deploy predictive models, machine learning algorithms, and statistical techniques, including natural language processing (NLP). Perform quantitative analysis to support scenario testing, stress testing, and thematic risk assessments. Ensure models are explainable, validated, and compliant with internal governance … business insights and decisions Proficiency in data visualisation and storytelling Understanding of model governance, validation, and explainability Familiarity with AI, prompt engineering, and large language model (LLM) applications Strong stakeholder engagement and communication skills in complex environments Qualifications Bachelor's or Master's degree in Data Science, Statistics, Computer ...

Data Scientist (NLP Deep Learning), Remote, UK About Revolut People deserve more from their money. More visibility, more control, and more freedom. Since 2015, Revolut has been on a mission to deliver just that. Our powerhouse of products including spending, saving, investing, exchanging, travelling, and more help our 75+ million … solve deep learning challenges Integrating cutting-edge AI technologies to drive innovation at Revolut What you'll need Experience in deep learning within natural language processing area and large language models A bachelor's degree in a STEM major (mathematics, computer science, engineering) Excellent knowledge ...

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 ...

from problem framing and data exploration through model development, application integration, deployment, and monitoring. Evaluate and implement appropriate approaches across machine learning, analytics, and natural language processing based on business needs and technical constraints. Partner with data and platform teams to build robust pipelines, reusable services ...

extracting insights from unstructured data for corporate or financial markets. Collaborate cross-functionally with political scientists, data scientists, and backend developers. Explain ML/NLP model outputs and methodologies to non-technical stakeholders. You May be a Good Fit if: Proven experience developing, refining, and monitoring machine learning models. Substantial … Would Make You Stand Out: Exposure to different cloud-based data and analytics platforms (e.g. AWS, DataBricks, Snowflake). Advanced degree or certification in NLP, ML, or related fields. Familiarity with DevOps practices and tools. Demonstrable impact of technical solutions or projects on decision-making Experience working in fast-paced ...

with people at all organizational levels of the firm Display a strong understanding and experience with emerging technologies, including generative artificial intelligence, machine learning, natural language processing, and their practical applications in a legal or corporate environment Possess a comprehensive knowledge of relevant AI and privacy legislation ...

client is a global leader in Generative AI SaaS, revolutionising how organisations create, manage, and optimise winning bids, tenders, and proposals using cutting-edge natural language processing technology. As one of the fastest-growing AI companies worldwide, they continue to scale rapidly to meet rising demand across ...

This UK-headquartered business is a recognised leader in digital due diligence and risk intelligence. Their proprietary technology blends AI and natural language processing to support clients across financial services, investment, and professional advisory sectors. With continued growth planned across 2026 and beyond, they're expanding their ...

LangChain, LangGraph Proven experience with Git, unit testing, containerisation and agile methodologies (Jira, Confluence) Good knowledge of generative AI, machine learning, deep learning or NLP Strong communication skills able to explain technical concepts to varied audiences Qualifications Bachelor's degree (Master's or PhD preferred) in Computer Science, AI, Data ...

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 ...

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 ...

APIs, prompt engineering, and retrieval augmented generation • Substantial depth and breadth across state-of-the-art AI/ML techniques such as Generative AI, NLP, and Deep Learning • Understanding of computer science fundamentals, computational complexity, and algorithm design • Ability to engineer and deploy well-architected software packages • Strong communication ...

similar agentic AI tooling) AWS/Azure cloud platforms (including AI services such as Bedrock) Data engineering tools (e.g. AWS Glue or equivalent) NLP, embeddings, vector databases, RAG architectures MLOps tooling for model deployment and monitoring Experience with distributed data systems and APIs Required Skills & Experience Several years' experience ...

driven applications. Key Responsibilities Design, develop and deploy AI and Machine Learning solutions into production environments Build and optimise Generative AI applications using Large Language Models (LLMs) Develop Retrieval Augmented Generation (RAG) architectures and AI agents Build speech-to-text, voice AI and accessibility-focused solutions Create intelligent chatbots … experience developing Machine Learning solutions Experience working with Large Language Models (LLMs) Knowledge of Generative AI technologies RAG (Retrieval Augmented Generation) implementation experience NLP and Conversational AI development Model training, testing and evaluation Prompt Engineering and AI workflow optimisation Programming & Frameworks Strong Python development skills PyTorch TensorFlow Scikit-Learn ...

model APIs, prompt engineering, retrieval augmented generation Substantial depth and breadth across state-of-the-art AI/ML techniques such as Generative AI, NLP, Deep Learning, etc. Understanding of CS fundamentals, computational complexity, and algorithm design Ability to engineer and deploy well-architected software packages Strong communication and stakeholder ...

experience building GenAI apps with LangChain and LangGraph, including agent design, state/memory management, and graph-based orchestration. Proficiency in ML/NLP and generative models; experience with embeddings, vector stores, RAG, and LLM integration/fine-tuning (OpenAI, LLaMA, Cohere, etc.) Strong coding in Python and experience with ...

proficiency in Python (NumPy, Pandas, SpaCy, scikit‐learn, PyTorch/TF2, Hugging Face Transformers). Understanding of ML & Deep Learning models, including architectures for NLP (transformers), GNNs, and multimodal systems. Solid understanding of database structures and SQL. Ability to perform independent research and synthesize current AI/ML research with … track record of applying new methods in production. Experience in end‐to‐end GenAI or advanced NLP projects such as NER, table extraction, OCR integrations, or GNN solutions. Familiarity with orchestration and deployment tools: Airflow, Redis, Flask/Django/FastAPI, SQL, R‐Shiny/Dash/Streamlit. Openness ...

recommend content and learning paths. You'll build models using diverse learning signals (written, spoken and behavioural data) and apply Machine Learning techniques across NLP, speech/audio and user interaction data. You'll have your voice heard, presenting your ideas to senior business stakeholders, defining 'undefinable' problems and uncovering ...

Computer Science, Statistics, Mathematics, Economics, or similar Working knowledge of statistical and machine learning methods (e.g. logistic regression, gradient boosting, random forests, clustering, NLP Proficient in Python and/or R, with strong experience in data quality, model development and feature engineering Strong command of SQL and familiarity with data ...

production features. ML Engineer/Applied Scientist – Own end‐to‐end ML projects from problem framing through to production deployment, specialising in a domain (NLP, vision, recommender systems, time‐series). Senior ML Engineer/Senior Scientist – Lead the technical design of major ML systems; mentor a small group ...

drive measurable business impact. Key Responsibilities Define the technical strategy for Data & AI initiatives across the business Lead the design and delivery of GenAI, NLP, Machine Learning and RAGbased solutions Translate complex business challenges into scalable AI products and capabilities Own architecture patterns covering orchestration, retrieval, monitoring, evaluation and governance ...