1 to 25 of 753 LLM Jobs in England

solutions for some of the world's largest law firms. In this role, you will leverage your deep expertise in machine learning, natural language processing, and large language model (LLM) agents to push the boundaries of legal technology. You'll be collaborating closely with data scientists, software engineers, and … product managers to integrate advanced NLP techniques into our products. What You'll Do Innovative NLP Research: Research, evaluate, and implement state-of-the-art NLP methodologies and large language model approaches to drive product innovation and develop new functionalities. LLM Agents & Multi-Agent Systems: Design, develop, and deploy LLM agents and multi-agent systems to automate complex legal workflows … to non-technical stakeholders. Proactivity & Continuous Improvement: Proactive in identifying problems, performance bottlenecks, and areas for improvement while taking pride in building and operating scalable, reliable, and secure systems. LLM Agents & Multi-Agent Systems: Proven experience in designing, deploying, and scaling large language model (LLM) agents and multi-agent systems to enhance NLP capabilities and automate complex workflows. Nice to More ❯

be essential for the role: Programming & Libraries: Deep proficiency in Python and extensive experience with relevant AI/ML/NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK). LLM Expertise: Proven experience developing applications leveraging state-of-the-art LLMs (e.g., GPT series, Llama series, Mistral, Claude) including prompt engineering, fine-tuning, and evaluation. GenAI & Agentic Frameworks: Hands-on More ❯

the Azure cloud. In this role you will You'll have the opportunity to work on a mixture of the following: Generative AI Design and develop RAG based applications LLM fine-tuning, including preparation of training sets from internal data Agent-based applications Evaluating use-case specific LLMs AI/ML Engineering NLP: Named Entity Recognition across a variety of More ❯

team members on code development. To Qualify for the Role, You Must Have As a Senior Data Scientist, you should have strong commercial development experience in developing and deploying LLM-based applications. Strong understanding of AI/ML algorithms, data science, and machine learning. Demonstrated proficiency in: Rapid prototyping of Data Science and Machine learning problems on large datasets. Building More ❯

fine-tune large language models (LLMs) and Generative AI systems. Integrate AI solutions with OpenAI services through Microsoft Azure. Expert or advanced-level expertise in at least one leading LLM that is competitive in the market. (OpenAI, GPT 4.0, turbo, etc) Research and implement machine learning algorithms and tools to solve complex problems. Develop pipelines for data preprocessing, training, validation More ❯

deep learning Excellent collaboration and communication skills, both with teams and in client-facing engagements Interested in building AI applications, ranging from forecasting tools to image recognition applications and LLM-based chatbots and agents Proven ability to build machine learning models and pipelines using Python and common ML and DL libraries ( Pytorch, Tensorflow) from early conceptualisation to full deployment in More ❯

such as Mlflow for model lifecycle management. Experience in building ML models in production using AWS ecosystem, especially ML related services such as SageMaker. Familiarity with large language models (LLM). Proficiency in multiple programming languages. Understanding of containerization technologies like Docker and orchestration tools like Airflow. We'vegot your back... We offer a range of total rewards that may More ❯

transformation goals and maximize their business impact through the effective use of data and AI. We leverage cutting-edge technologies in data analytics, data governance, AI-ML, GenAI/LLM and industry best practices to deliver custom solutions that help organizations optimize their operations, enhance customer experiences, and drive growth. Job role: Senior Software Engineer - PriceFX Implementation Years of Experience More ❯

hear from you. Your responsibilities Collaborate with engineering, data science, and AI teams to develop AI-powered capabilities. Evaluate AI model performance through testing and experimentation. Deploy and improve LLM-based applications in production. Integrate AI capabilities into production systems, ensuring scalability and efficiency. Stay updated with AI and ML advancements and suggest improvements. Work with cross-functional teams to More ❯

knowledge of CI/CD practices, ML Ops, ML pipelines, automated testing, and platforms such as AzureML, Google Cloud, or AWS. Possess hands-on experience in using and developing LLM-powered applications, including retrieval-augmented generation (RAG), prompt engineering, and fine-tuning. Produce high-quality, coherent documentation to support their work, even though formal research output is not expected. Prior More ❯

Why This Role Stands Out: This opportunity will enable you to lead transformative AI products that go beyond dashboards and models,powering real-time automation, autonomous decision making, and LLM-driven innovation. Join an organisation investing heavily in next-gen AI, with an open mindsetfor experimentation and thought leadership. More ❯

classification) and deploying them as APIs/services. Strong skills in MLOps: containerisation (Docker, Kubernetes), cloud deployment (AWS, GCP, Azure), and CI/CD pipelines. Experience with prompt engineering, LLM evaluation, and vector databases (Pinecone, Weaviate, FAISS). Excellent communication skills and cross-functional collaboration experience. Benefits: Our team at OneClickComply is central to our 100% customer satisfaction, and we More ❯

tools (Spark, Hadoop), ETL workflows, or high-throughput data streams Genomic data formats and tools Cold and hot storage management, ZFS/RAID systems, or tape storage AI/LLM tools to accelerate data workflows What you’ll get in return: You’ll join a purpose-driven start-up doing incredibly meaningful work, with a flexible, remote-first culture and More ❯

tools (Spark, Hadoop), ETL workflows, or high-throughput data streams Genomic data formats and tools Cold and hot storage management, ZFS/RAID systems, or tape storage AI/LLM tools to accelerate data workflows What youll get in return: Youll join a purpose-driven start-up doing incredibly meaningful work, with a flexible, remote-first culture and the autonomy More ❯

and technologies (e.g., Kafka, Azure Event Hubs, Kinesis). Knowledge of handing Genome datasets (FASTQ, VCF etc.) and document formats (IHE). General experience working with Gen AI including LLM generated clinical data/summaries Experience Extensive background as a data engineer, specialising in data warehouse environments and building various types of data pipelines. Demonstrated ability to design and implement More ❯

format open-source data. Model data for humans & machines. Draft schemas across SQL, NoSQL, graph, and search systems so analysts and algorithms can both fly. Innovate. Evaluate and integrate LLM and other AI based solutions to improve data extraction and analysis across Kharon's products. Partner with the doers. Sit with product managers, data scientists, investigators, and sanctions experts - translate More ❯

Jenkins. Exposure to security frameworks (NIST, ISO 27001, SOC 2). Experience working in SaaS, multi-tenant cloud environments. Knowledge of machine learning security (AI/ML model risks, LLM security best practices). Familiarity with attack surface management and threat intelligence. Relevant certifications (e.g., Security+, SSCP, GSEC) are a plus but not required. What do we offer? We value More ❯

and Python test suites (e.g. pytest) Experience using generative models, prompting and testing at scale Familiarity with best practices in AI Engineering, to include differences in prompts between major LLM vendors. Ability to develop and maintain good working relationships with cross-functional teams. Ability to clearly communicate and present to internal and external stakeholders. Nice to have, but not essential More ❯

deploying machine learning solutions in production environments. Strong track record of successfully translating academic research into real-world applications and products. Ability to estimate suitability of candidate ML, NLP, LLM, and GenAI technologies for specific scenarios, estimate the time, cost and outcomes of different solutions, and apply effective risk management to ensure prompt delivery Deep experience in Python and PyTorch More ❯

AI engineering projects utilising LLMs that you're proud of in your application. Ideally these projects should show off complex and clever architectures or a systematic evaluation of an LLM's behaviour. You might be a good fit if you Bring your deep-dive software engineering expertise Thrive in a results-driven environment, where flexibility fuels impact Be a game More ❯

is a hands-on, impactful role within a newly formed GenAI team, with plenty of opportunity to influence tooling, architecture, and strategy. Key Responsibilities: Design and deliver NLP and LLM-based algorithms tailored to internal user needs Apply RAG methods to provide accurate, context-rich AI responses using internal data Work with stakeholders across engineering, manufacturing, and systems teams to More ❯

multi-threaded asynchronous C++ or Go development. You have prior experience in one of: resource orchestrators like slurm/kubernetes, high performance computing, building scalable systems, experience in large language model training. This is a great team to come to have a huge impact on AWS and the world's customers we serve! A day in the life Every day More ❯

internal and client projects. You will be involved in: Applying data science best practices and standards across projects. Assisting in the design and implementation of Generative AI applications, including LLM workflows, RAG architectures, and prompt engineering. Collaborating with stakeholders to identify opportunities where GenAI can streamline tasks, automate insights, or improve decision-making. Gathering, processing, and managing data from disparate More ❯

of machine learning principles, deep learning techniques and GenAI concepts such as prompt engineering, chain-of-thought reasoning, prompt chaining, Retrieval-Augmented Generation (RAG), custom-built agents. Familiarity with LLM and agentic frameworks like LangChain, PydanticAI, or similar. Proficiency in ML-Ops practices and tools; strong understanding of DevOps and CI/CD. Experience with cloud platforms, e.g. AWS (preferred More ❯

Knowledge, Skills and Abilities Strong programming skills in Python, R, or similar languages, with experience in modern ML frameworks (PyTorch, TensorFlow). Demonstrated experience with generative AI technologies, including LLM architectures and frameworks. Experience with natural language processing and generative AI for medical text analysis, generation, and interpretation. Demonstrated ability to build relationships with stakeholders and subject matter experts. Familiarity More ❯