226 to 250 of 297 Natural Language Processing Jobs in London

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 ...

improves over time. We are looking for a mid-level Data Scientist to join the team that owns business-critical, live solutions utilising Large Language Models (LLMs), such as an email ingestion/extraction solution and underwriting agents. This is not a pure research or offline-modelling role - when … designing experiments, engaging with stakeholders and collaborating with engineers to deliver production solutions. You'll have: Experience working in Data Science, Applied Machine Learning, NLP or LLM-focused roles. Strong Python and SQL skills, with experience working in production codebases and collaborative engineering environments. Hands-on experience evaluating, deploying ...

practices, system design, application development, testing, and operational stability. Experience integrating AI/ML techniques into software systems, including familiarity with LLMs, Generative AI, NLP, RAG, AI evals, and coding assistants. Managing and mentoring software engineering or AI/ML teams, with experience as a hands-on practitioner delivering production … operational stability. Preferred Qualifications, Capabilities, and Skills: Experience working at code level with advanced AI/ML business applications (e.g., LLMs, Generative AI, NLP). AWS Certifications (Solution Architect Associate or Professional) are advantageous. In-depth knowledge of the financial services industry and their IT systems. Practical cloud native experience. ...

practices, system design, application development, testing, and operational stability. Experience integrating AI/ML techniques into software systems, including familiarity with LLMs, Generative AI, NLP, RAG, AI evals, and coding assistants. Managing and mentoring software engineering or AI/ML teams, with experience as a hands-on practitioner delivering production … operational stability. Preferred Qualifications, Capabilities, And Skills Experience working at code level with advanced AI/ML business applications (e.g., LLMs, Generative AI, NLP). AWS Certifications (Solution Architect Associate or Professional) are advantageous. In-depth knowledge of the financial services industry and their IT systems. Practical cloud native experience. ...

product use. Develop, compare and validate appropriate statistical and machine-learning models for classification, ranking, recommendation, forecasting, anomaly detection, similarity or extraction problems. Use NLP, embeddings and LLM-assisted techniques responsibly for classification, entity resolution, information extraction, clustering and relationship discovery across document-heavy data. Publish curated datasets, features … controls in Microsoft Fabric and Databricks. Strong grounding in exploratory data analysis, statistics, feature engineering, model selection, validation and error analysis. Practical experience with NLP, information extraction, entity resolution, embeddings or other techniques relevant to document-heavy and relationship-rich data. Good understanding of data lineage, provenance, metadata, access controls ...

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 ...

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 ...

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. ...

including embedding pipelines, RAG workflows and text analysis models. Develop and deploy agentic and multicomponent AI systems using modern ML frameworks. Engineer high performance NLP and sequence models for information extraction, classification and risk prediction. Engineering level platform configuration Configure advanced OneView components linked to modelling outputs such as risk … machine learning engineering Strong Python engineering skills and experience with modern ML frameworks Practical experience training and evaluating models (tree based, temporal, embedding/NLP or LLM based) Ability to build reproducible training and evaluation pipelines Experience containerising and deploying models (e.g., Docker, Fast API) Solid data and database 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 … 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 ...

member of our research and development efforts, you will play a crucial role in advancing the state-of-the‐art in Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), Computer Vision and GenAI technologies for law enforcement and beyond. You will collaborate with cross‐functional teams … data sources. Design and implement efficient and scalable MLLM models for inference and analysis of multimodal data. Explore novel approaches to address challenges in NLP, NLU, Object Detection, Object Recognition, Object Tracking, Segmentation, and Scene Understanding. Optimize AI models, algorithms for performance, memory footprint, and energy efficiency to meet ...

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 ...

intensive applications operating at scale. Develop Event-Driven Architecture: Help move our architecture from scheduled pipelines towards real‐time services using messaging, queues, asynchronous processing and distributed workflows. Build Systems for AI Agents: Develop the production software required to run increasingly agent‐driven AI workflows, including state management, task … Kubernetes/EKS, ECS, Docker, RDS/PostgreSQL and S3. Productionise AI Workloads: Work closely with our AI engineers to deploy and operate NLP, LLM and quantitative‐model workloads, including workloads using our in‐house GPU infrastructure. Own Software Through to Production: Take responsibility for testing, deployment, performance, monitoring ...

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 ...

Permutable, we’re building intelligent systems to automate market analysis using advanced NLP and multi-LLM frameworks. Our goal is to dramatically accelerate how financial information is processed, understood, and acted on, enabling faster, smarter decisions for financial analysts. As a small, ambitious startup, you’ll work directly with … software systems – develop scalable backend services and APIs that power our AI-driven applications. Develop & Optimise data pipelines – implement efficient, reliable systems for ingesting, processing, and serving financial data. Engineer Cloud-Native Solutions on AWS (Lambda, ECS/EKS, S3, Redshift, etc.) and automate deployments with GitHub Actions & Pulumi. ...

anomaly detection. You need to know the concept and be handy with the most common libraries Model Hosting and Monitoring: Host and monitor NLP models and LLM for real-time and batch inference. Develop Monitoring Systems: Create and support robust models for monitoring. Support and Innovate: Assist with a long … with third-party APIs is essential. Data Pipelining: Experience with SQL, ETL, data modeling. Experienced with the lifecycle of building ML solutions Speak AI language: Understand the fundamentals of ML/AI and communicate effectively with AI and Data Scientists. Infra: Deep Knowledge of Docker, Git, cloud networking ...

Demonstrating the value and potential of AI and advanced analytics through workshops, presentations and client engagements Applying modern data science techniques including statistical modelling, NLP, time-series analysis, spatial analysis and mathematical modelling Collaborating with multidisciplinary teams to deliver high-quality solutions in a fast-paced consulting environment Contributing … Data Scientist, AI Consultant, Machine Learning Consultant, GenAI Consultant, AI Engineer, Applied Data Scientist, Analytics Consultant, ML Engineer, Data & AI Consultant, Advanced Analytics Consultant, NLP Specialist, Python Developer, AI Transformation Consultant, Databricks Consultant, Azure AI Consultant, AWS Data Scientist, GCP Data Consultant, Agentic AI Consultant, OpenAI GPT Specialist, PySpark Developer. ...

enterprise use. Analytics, AI and Agentic Strategy Prioritisation Prioritise data access, tooling and platform capabilities required to support advanced analytics, AI/ML, NLP, intelligent automation and agentic strategies for the group. Identify opportunities to deploy production-grade analytics and AI-enabled solutions that improve decision-making, risk transparency, operational … modelling, semantic layers, canonical data views, data catalogues, data quality, lineage, metadata, critical data elements and data governance frameworks. Understanding of AI/ML, NLP, intelligent automation, agentic AI concepts or production-grade analytics, with the ability to distinguish credible business use cases from experimentation. Proven ability to translate abstract ...

specifically for agent applications. This allows us to achieve the best performance at a given inference cost. Our work spans the development of Large Language Models (LLMs) and Vision-Language Models (VLMs), enabling agents to perceive, understand, and act within complex environments. We own the entire pipeline including … tier AI conferences (e.g., NeurIPS, ICML, CVPR, ACL, ICCV, AAMAS, ...) Advanced degree (PhD or MSc) in a relevant field (e.g., ML, DL, NLP, CV) Experience with large-scale distributed training and inference (multi-node, large models, MoE, parallelism strategies, etc) Experience training models for computer use or other multi ...

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 … collaborate across teams, while staying grounded in product impact, user experience, and real-world performance. Nice to have Experience with machine translation, multilingual NLP, efficient long-context modeling, language quality estimation, or multimodal machine translation. Experience designing evaluation and reward signals using automatic metrics, Model-as-judge evaluation ...

that enable safe and efficient use of Generative AI at scale. We create services, applications and libraries that power the use of Intelligent Document Processing to drive real-world business impact. The Role This is a senior role within a deliberately flat team structure. You will be expected … require novel solutions but are constrained by regulatory and compliance requirements. Experience building production systems for one or more of: document/data extraction, NLP-based classification, machine translation, fraud or anomaly detection, or workflow automation. Experience evaluating the performance of Generative AI applications – exposure to Mlflow, experiment design, evaluation ...

taking AI and agentic systems from prototype to production Strong understanding of infrastructure, authentication, and observability Experience delivering high-stakes consulting engagements across multiple language paradigms, stacks, ecosystems, and client industries Experience with multiple languages and frameworks, including Java, C#/.NET, Python, TypeScript, JavaScript … React, Go, Ruby, Scala, R, and SQL Experience experimenting with AI development tools Experience building or integrating AI/ML features, including recommendation engines, NLP, computer vision, predictive analytics, RAG pipelines, and agents Experience leading modernisation and replatforming efforts Experience solving architecture-level problems involving scalability, security, reliability, performance, maintainability ...