51 to 67 of 67 Natural Language Processing Jobs in London

Skills & Experience RAG Engineering (must-have) ● 6+ years of software engineering experience, with at least 2-3 years focused on information retrieval, search systems, NLP, or RAG architectures. ● Deep expertise in vector databases — production experience with at least one of: Pinecone, Weaviate, Milvus, Qdrant, Chroma, pgvector, or Databricks Vector Search. … Master's degree in Computer Science, Information Retrieval, Computational Linguistics, Data Science , or a related quantitative discipline. PhD in a relevant field (IR, NLP, knowledge graphs) is a strong differentiator. ● Relevant certifications are valued (Databricks Certified, AWS/Azure ML Specialty) but are secondary to demonstrated hands-on expertise. Agents ...

innovation . This is a long-term contract opportunity where you’ll work on real-world, production-grade AI solutions , including LLM-powered applications, NLP pipelines, and emerging agentic systems . You’ll be operating in a highly data-driven environment, solving complex business problems and delivering impactful … cases at scale. Key Responsibilities Build, deploy, and optimise machine learning and NLP models in production Develop end-to-end data science pipelines Design and prototype Generative AI solutions (LLMs, embeddings, prompt engineering) Work with BigQuery ML and cloud platforms for large-scale modelling Translate business challenges into scalable data ...

technical requirements Facilitate workshops and discovery sessions to co-create solutions Technical Expertise Maintain a strong understanding of AI/ML technologies (e.g., NLP, generative AI, predictive modelling) Guide architectural decisions for AI platforms, data pipelines, and integration Stay up to date with emerging AI trends and assess their applicability … Machine Learning, Computer Science, or related field Experience with cloud platforms (e.g., AWS, Azure, GCP) and AI services Familiarity with generative AI and large language models Experience in driving organisational change and technology adoption Key Success Metrics Successful delivery of AI use cases into production Measurable business impact from ...

well-defined modelling tasks. Build end to end ML pipelinesfrom feature engineering and preprocessing to deployment ready model outputs. Apply advanced techniques such as NLP, time series forecasting, anomaly detection, optimisation, or LLM/GenAI methods where relevant. Implement model evaluation frameworks using offline metrics, cross validation, online experiments … connectivity and Data Integrations Experience working with large, complex datasets, including data cleaning, feature engineering, and exploratory data analysis. Familiarity with LLMs, NLP techniques, and GenAI frameworks, including embeddings, prompt engineering, or fine tuning. Experience building end to end ML pipelines, including model validation, optimisation, deployment, and monitoring. Understanding ...

Senior AI Engineer (NLP/LLMs) – remote (UK based) £70-100k depending on experience A high-growth SaaS company is hiring a Senior AI Engineer to help build intelligent, mission-critical systems used in highly regulated environments. The platform applies machine learning and large language models across complex … data workflows, solving real-world problems with measurable social impact. The Role As a Senior AI Engineer, you’ll design, build and deploy advanced NLP and LLM-based solutions, taking models from research through to production. You’ll work closely with AI, data, MLOps and product teams to translate business ...

engineering roadmap aligned to Banking tech strategy and enterprise architecture. AI Engineering & Architecture – Lead the design and development of scalable AI systems using LLMs, NLP, knowledge graphs, and machine learning pipelines. Architect secure, compliant AI solutions that integrate with market data, CRM, internal knowledge bases, and document repositories. Data Strategy … financial services or enterprise environments. Demonstrated success building AI applications in investment banking, asset management, or capital markets domains. Deep expertise in ML, NLP, LLMs, retrieval‐augmented generation (RAG), embeddings, and modern MLOps practices. Strong experience working with both structured financial datasets and unstructured data sources (e.g., filings, call transcripts ...

Python/Django) About the role: We are working with an early-stage, AI-driven technology company building advanced platforms that leverage machine learning, NLP and large language models to solve complex research and data problems. The team is focused on developing scalable, intelligent systems , increasingly incorporating LLM-powered … design and backend architecture Proficiency with Git Willingness to work 2 days per week onsite in London Nice to have Exposure to NLP or search systems (e.g. semantic search) Experience working with LLMs or generative AI Frontend experience (e.g. React ) Experience with Elasticsearch or OpenSearch Experience with AWS or similar ...

office 5 days per month. As ML Engineer, your mission is to: Participate in the continuous improvement of our client's products Develop advanced NLP and AI-based products that will delight users Provide excellence in cloud-based ML engineering, with as much focus on Operations as Development. Expand … demonstration and documentation Key Responsibilities As a machine learning engineer, your main responsibility is to conduct the development and productionisation of ML and NLP-based features for the client's products - a SaaS Platform and an API. Develop optimal ML & NLP solutions for use cases, from baseline to SOTA approaches ...

APIs. Run technical experiments to test new AI-powered workflows, notably using Agentic AI. Engineer prompts and automation pipelines for AI-assisted localization. Leverage NLP/NLU techniques to improve localization automation, translation quality evaluation, and multilingual content understanding across Expedia Group experiences. 3. Machine Translation and linguistic systems Develop … programming skills (Python, Java, JavaScript/TypeScript) REST APIs, testing tools Regex and string handling Solid knowledge of Unicode, ICU & CLDR Working knowledge of NLP and NLU concepts: tokenization, embeddings, classification, sequence labeling, semantic similarity, intent/entity extraction Experience building production services, scripts, or internal platforms. Experience working with ...

Staff Machine Learning Engineer – NLP/Search/LLMs London (Hybrid – 2 days onsite) £90,000 – £110,000 + Equity I'm working with an AI-first technology platform transforming how complex intellectual property research is done using LLMs, NLP and advanced search systems . They were early adopters … building agentic AI workflows that can autonomously answer complex research questions. They're looking for a Staff ML Engineer to help scale their NLP and search capabilities . What you'll be doing • Improving search quality (precision & recall) across large datasets • Designing LLM-powered workflows and agentic systems • Building ...

automation across entity matching, data validation, and workflow orchestration using AI/ML. Implement agentic AI and LLM-based services to streamline onboarding, document processing, and exception handling. Ensure compliance with data privacy, data sovereignty, and regulatory architecture patterns (e.g., regional sharding, zero-data copy patterns). Bring … CloudWatch, API Gateway, ECS, ECR, SQS, SNS). Familiarity with Open AI APIs, Agentic AI – Crew/LangChain/RAG/AutoGen/NLP/Java/Python/REST/Telemetry/Security/Auditability. Domain knowledge in client onboarding, KYC, and regulatory workflows, with a deep understanding ...

Build, train, and optimise machine learning models used by financial services clients and quant teams. • Develop LLM‐based solutions including finetuning, conversational agents, and NLP‐to‐LLM pipelines. • Contribute to proprietary data assistance products designed for analytical workflows. • Work across Python‐based modelling, experimentation, and error analysis. • Collaborate closely with … trading‐focused models. • Experience building ML models end‐to‐end, including optimisation and error analysis. • Knowledge of LLMs, finetuning, conversational AI, or modern NLP techniques. • Comfortable working in a collaborative environment with engineers and product teams. What They Offer • Opportunity to work directly with senior leaders and impact product direction. ...

relevant experience Advanced degree in a quantitative field such as data science, statistics, mathematics, physics or engineering Strong knowledge in statistics, machine learning, NLP or AI techniques is a plus Capacity to multi-task in a fast paced environment while keeping strong attention to detail Coding skills required … least one leading programing language (Python, R, Matlab and/or C++, C#) Experience in exploring large datasets across multiple time frames is a plus Intellectual curiosity to explore new data sets, solve complex problems, drive innovative processes and connect the dots between multiple fields Capacity to work with ...

post-go-live support. There is also an opportunity to contribute to the integration of broader intelligent automation technologies, including Machine Learning, OCR and NLP, within an established governance framework. Key responsibilities Design, develop and deliver end-to-end automation solutions Review Process Definition Documents (PDDs) and produce Solution Design … Documents (SDDs) Develop Power Automate cloud workflows, RPA workflows and hybrid automation solutions Integrate intelligent automation capabilities such as ML, OCR and NLP where appropriate Support SIT and UAT, including preparation of test plans and test data Work closely with technical and change teams to ensure access, requirements and dependencies ...

executive presentations. Positioning Zendesk as the customer’s platform of choice.* **Champion AI & automation:** Translate advanced AI/ML capabilities (including LLMs, ChatGPT, NLP, and predictive analytics) into actionable CX strategies that increase efficiency, personalisation, and scalability.* **Influence product evolution:** Leverage customer insights to inform product innovation, shape reference architectures … Contact Center, Customer Service software, ITSM, Business Intelligence, Data Warehousing, Workforce Management, QA or Integration & Middleware.* Strong understanding of AI and automation technologies (LLMs, NLP, ChatGPT, MCP, predictive analytics) and their impact on customer service transformation.* Demonstrated ability to lead virtual teams to successful outcomes and build consensus across technical ...

development of automation processes. You will work with cutting-edge technology, integrating intelligent automation capabilities (such as Machine Learning, OCR, and NLP) into scalable workflows. Key Responsibilities Development: Design, develop, and implement enterprise-grade automations using Power Automate (cloud flows, desktop flows/RPA, and combined workflows). Solution Design … User Acceptance Testing (UAT), ensuring automations are robust, fit-for-purpose, and align with governance frameworks. Integration: Integrate intelligent automation capabilities (AI, OCR, NLP) into automated processes to enhance functionality. Handover: Manage the smooth transition of automations to the support team during Post Go-Live Support (PGLS), ensuring comprehensive knowledge ...

deploying ML-powered features across a production platform Working across Python and TypeScript, integrating models into scalable, real-time systems Fine-tuning and training NLP models using techniques like transformers Driving the machine learning strategy and building best practices from the ground up Collaborating closely with product, engineering, and leadership … looking for: Strong commercial experience building and deploying ML models in production Proficiency in Python and familiarity with TypeScript/JavaScript Experience with NLP or recommendation systems is a bonus Excited by start-ups: product-minded, hands-on, and motivated by impact What's on offer ...