15 of 15 Permanent Information Retrieval Jobs in London

GBR-London-5 Canada Squaretime type: Full timeposted on: Posted Todayjob requisition id: JREQ194360 London is seeking scientists with a passion for solving problems using state-of-the-art information retrieval, natural language processing and generative AI. About the Role Lead Applied Scientists are experts in NLP/IR/ML/GenAI, responsible for the design and … delivery of AI solutions that enhance Thomson Reuters' products. They leverage information retrieval techniques, prompting workflows, model training and evaluation design to build and optimize solutions. Their work ensures AI technologies are effectively aligned with business objectives, driving product innovation and value. As a Lead Applied Scientist, you will: Lead an applied research team throughout the full product … with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world.Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. More ❯

MSc. Background Generative AI (GenAI) is seen as having the potential to revolutionise our client’s operations across all major lines of business. Applications may include conversational AI, intelligent information retrieval, AI-assisted system design, intelligent plant monitoring, and autonomous exploratory systems. We’re seeking a Data Scientist with good hands on python skills and a focus on … Processing (NLP) to contribute to innovative R&D efforts within the GenAI/NLP team. This role will focus on the application and development of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, and domain-specific GenAI solutions to support key internal use cases and products. Responsibilities In this role you will: Design, implement and maintain scalable NLP … state-of-the-art research in the space of LLMs/NLP, proposing new ideas and methodologies that unlock business value. Contribute to the development of RAG systems and retrieval pipelines, including chunking, embedding, re-ranking, and evaluation. Participate in experiments, including designing experimental details, writing reusable code, running evaluations, and organising results. Collaborate with a team and help More ❯

a culture of innovation, experimentation, and scientific rigor. Stay on top of industry trends and emerging technologies in AI/ML, particularly in GenAI, Search, RecSys, and Personalisation. Search & Information Retrieval Lead the development and optimization of scalable search systems, including relevance tuning, semantic search, and ranking algorithms. Integrate LLMs and transformer-based models to enhance search accuracy More ❯

a culture of innovation, experimentation, and scientific rigor. Stay on top of industry trends and emerging technologies in AI/ML, particularly in GenAI, Search, RecSys, and Personalisation. Search & Information Retrieval Lead the development and optimization of scalable search systems, including relevance tuning, semantic search, and ranking algorithms. Integrate LLMs and transformer-based models to enhance search accuracy More ❯

a culture of innovation, experimentation, and scientific rigor. Stay on top of industry trends and emerging technologies in AI/ML, particularly in GenAI, Search, RecSys, and Personalisation. Search & Information Retrieval Lead the development and optimization of scalable search systems, including relevance tuning, semantic search, and ranking algorithms. Integrate LLMs and transformer-based models to enhance search accuracy More ❯

a culture of innovation, experimentation, and scientific rigor. Stay on top of industry trends and emerging technologies in AI/ML, particularly in GenAI, Search, RecSys, and Personalisation. Search & Information Retrieval Lead the development and optimization of scalable search systems, including relevance tuning, semantic search, and ranking algorithms. Integrate LLMs and transformer-based models to enhance search accuracy More ❯

NLP and Machine Learning, responsible for the design and delivery of AI solutions that enhance Thomson Reuters' products. They leverage model training and evaluation design, graph-based AI, and information retrieval techniques, and prompting workflows, to build and optimize solutions. Their work ensures AI technologies are effectively aligned with business objectives, driving product innovation and value. As an More ❯

is that you will be deeply involved with productionising and deploying. Strong Python, SQL and programming skills Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including More ❯

is that you will be deeply involved with productionising and deploying. Strong Python, SQL and programming skills Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including More ❯

is that you will be deeply involved with productionising and deploying. Strong Python, SQL and programming skills Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including More ❯

is that you will be deeply involved with productionising and deploying. Strong Python, SQL and programming skills Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including More ❯

prompt engineering, fine-tuning (e.g., LoRA/PEFT), vector search, and RAG-based services Great knowledge of NLP algorithms: tokenisation, embeddings, attention, language modelling, text classification/generation, and information retrieval Desirable Skills 👌 Can speak, or learning to speak, more than one language Experience with reinforcement learning Knowledge-sharing experience (tech talks, articles, YouTube videos, etc.) Experience using More ❯

prompt engineering, fine-tuning (e.g., LoRA/PEFT), vector search, and RAG-based services Great knowledge of NLP algorithms: tokenisation, embeddings, attention, language modelling, text classification/generation, and information retrieval Desirable Skills 👌 Can speak, or learning to speak, more than one language Experience with reinforcement learning Knowledge-sharing experience (tech talks, articles, YouTube videos, etc.) Experience using More ❯

prompt engineering, fine-tuning (e.g., LoRA/PEFT), vector search, and RAG-based services Great knowledge of NLP algorithms: tokenisation, embeddings, attention, language modelling, text classification/generation, and information retrieval Desirable Skills 👌 Can speak, or learning to speak, more than one language Experience with reinforcement learning Knowledge-sharing experience (tech talks, articles, YouTube videos, etc.) Experience using More ❯

prompt engineering, fine-tuning (e.g., LoRA/PEFT), vector search, and RAG-based services Great knowledge of NLP algorithms: tokenisation, embeddings, attention, language modelling, text classification/generation, and information retrieval Desirable Skills 👌 Can speak, or learning to speak, more than one language Experience with reinforcement learning Knowledge-sharing experience (tech talks, articles, YouTube videos, etc.) Experience using More ❯