51 to 75 of 111 Natural Language Processing Jobs in the UK

accelerates, and we’re now scaling our team to meet that demand. The Role We’re looking for a Senior AI Engineer (FinLLM/NLP) to help drive the next generation of AI systems powering financial services. This role focuses on developing, fine-tuning and deploying advanced language models … that operate at production scale within highly regulated environments. You’ll work alongside our NLP team, software engineers, and product leaders to build cutting-edge solutions that transform how financial organisations use AI. This is a hands-on role where you’ll shape both the technical direction and practical deployment ...

currently have a phenomenal opportunity for an AI Engineer to join our us as we enhance our customer experience by harnessing the power of NLP, large language models, and flawless integration with third-party GenAI services. In this dynamic role, you'll be involved in every stage … business. PhD or MSc experience in a numerate subject: Machine Learning, Computer Science, Statistics, or equivalent, Demonstrable experience of applying, researching, and developing sophisticated NLP models, prompt engineering + fine-tuning LLMs to drive value in a commercial setting, Able to work independently and efficiently to deliver projects on time ...

high-performing lean teams. People-first leadership style, with a proven ability to build and nurture high-performing teams. Exposure to machine learning, NLP, or financial data products is highly advantageous. Comfortable working in fast-moving, ambiguous environments where both execution and strategic vision matter. Additional Info ...

text, images, metadata). What you’ll do Build & productionise ranking, recommendation, and pricing models Design A/B tests and experimentation frameworks Apply NLP, LLMs, and vector databases to real product problems Create multi-step AI workflows for commercial and operational decisions Translate technical insights into product & revenue impact ...

Data Governance and Data Catalog solutions: Axon, Informatica EDC, Colibra, Purview, etc. Previous experience in Artificial Intelligence techniques: ML/Deep Learning, Computer Vision, NLP, etc General information: Start Date: ASAP Length of Contract: 1 year (minimum) Work Location: Madrid Remote working. (It may be necessary at some point ...

Bring Must‐Haves Strong Python engineering skills and experience shipping AI/ML systems into production. Hands‐on experience with LLMs, RAG, Transformers, or NLP/IR architectures. Experience with prompt engineering, evaluation, and optimisation techniques. Comfortable working with cloud infrastructure (AWS/Azure/GCP). Knowledge of MLOps ...

What you will do as a Senior ML Engineer Design, build, and optimise machine learning models, including NLP, computer vision, and predictive analytics. Own the ML lifecycle from data preparation through training, evaluation, and deployment. Implement and maintain MLOps workflows for continuous integration and delivery of ML models. Collaborate with … with cloud platforms (AWS) and containerisation (such as Docker, Podman, Kubernetes). Exposure to big data technologies (Spark, Hadoop) and Apache tools. Knowledge of NLP, computer vision, and deep learning architectures. Familiarity with Agile and DevOps practices. STEM degree or equivalent experience in AI, Data Science, or related fields. Industry ...

secure, high-integrity systems and services across critical defence, government, and public sector programmes. Key Responsibilities: Design, build, and optimise machine learning models, including NLP, computer vision, and predictive analytics Own the ML lifecycle from data preparation through to training, evaluation, and deployment Implement and maintain MLOps workflows for continuous … data technologies (Spark, Hadoop) and Apache tools Familiarity with Agile and DevOps practices Industry certifications (e.g., TensorFlow Developer, AWS Machine Learning Specialty) Knowledge of NLP, computer vision, and deep learning architectures STEM degree or equivalent experience in AI, Data Science, or related fields If you are ready to take ownership ...

that directly improve customer outcomes. Key Responsibilities • Own 0-1 ML product development from prototype to production • Build and scale LLM systems (RAG, agents, NLP) • Translate product needs into experiments, MVPs, and production features • Collaborate with Engineering and Product to ship solutions • Work with large-scale cloud datasets to drive ...

science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning). Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we have built ...

building and leading teams of experienced ML engineers/scientists. Solid understanding of the fundamentals of statistics, optimization, and ML theory, focusing on NLP and/or Computer Vision algorithms. Hands‐on experience in implementing distributed/multi‐threaded/scalable applications (incl. frameworks such as Ray, Horovod, DeepSpeed, etc. ...

e.g., Jira) Hands-on experience with a range of databases and storage technologies: Elastic, Mongo, Cassandra, Redis, S3 Desirable Skills PyTorch, AI/ML, NLP, LLMs Experience with the Atlassian Suite, GitHub, Linux CLI Broader data handling and advanced model-driven development exposure To learn more, please do reach ...

e.g., Jira) Hands-on experience with a range of databases and storage technologies: Elastic, Mongo, Cassandra, Redis, S3 Desirable Skills PyTorch, AI/ML, NLP, LLMs Experience with the Atlassian Suite, GitHub, Linux CLI Broader data handling and advanced model-driven development exposure To learn more, please do reach ...

platforms, ML pipelines, and AI products Ensure solutions are scalable, reusable, secure, and cost effective Select appropriate ML/AI techniques (e.g., regression, classification, NLP, forecasting, clustering) 2. Data & Analytics Engineering Alignment Work closely with data engineers to define: Data models and schemas Data quality rules ETL/ELT pipelines … Establish best practices and reusable design patterns Your Profile Essential Skills/Knowledge/Experience Data Science & ML Supervised and unsupervised learning Time series, NLP, recommendation systems (as applicable) Programming Python (NumPy, Pandas, Scikit learn) Optional: R, SQL Data Platforms Relational & NoSQL databases Big data frameworks (Spark, Hive, Databricks) MLOps ...

will be required to go through MOD SC clearance. You will be involved in: Design, build, and optimise machine learning models, including NLP, computer vision, and predictive analytics Own the ML lifecycle from data preparation through training, evaluation, and deployment Implement and maintain MLOps workflows for continuous integration and delivery ...

quantitative field. Fluent Python programmer with experience in deep learning frameworks (e.g., PyTorch). Expert in core data science techniques (supervised/unsupervised, NLP) and developing innovative algorithms. Leadership mindset, mentoring teams and fostering collaboration. Commercially aware, able to translate complex business problems into practical, high-quality solutions. ...

using Infrastructure as Code, with a strong focus on automation, compliance and best practice. Develop and integrate AI applications and services, including classical ML, NLP, RAG and generative AI solutions. Support experimentation and proof-of-concept work through secure AI sandboxes and evaluation of emerging tools and platforms. Monitor, optimise ...

Machine Learning, AI, Data Science, Engineering and SaaS – ideally 3-4 years. Experience managing teams from technical standpoint including people management. Confident working with NLP, LLM type solutions. Strong technical background in Data, Development & Cloud – Python/Azure. High level stakeholder management skills. Must have recent FinTech or Finance experience. ...

services, or complex enterprise environments Right to work in the UK Desirable Skills & Experience Exposure to AI/ML concepts (e.g. machine learning models, NLP, RPA, decision intelligence) Experience with data platforms, cloud ecosystems, or analytics tools Knowledge of post-merger integration (PMI) frameworks Agile certifications (e.g. Scrum, SAFe ...

will be required to go through MOD SC clearance. You will be involved in: Design, build, and optimise machine learning models, including NLP, computer vision, and predictive analytics Own the ML lifecycle from data preparation through training, evaluation, and deployment Implement and maintain MLOps workflows for continuous integration and delivery ...

modern automation tooling. Exposure to testing data-driven applications and distributed systems. Desirable: Experience testing GenAI or LLM-based services. Background in supporting ML, NLP, or data-heavy engineering environments. Familiarity with validating prompt flows, LLM responses, or AI pipelines. Tech Environment: Python, JavaScript, Node.js Performance automation tools API testing ...

stack including Microsoft Fabric and Azure Basic understanding of data science principles such as machine learning, cluster analysis etc. as well as generative AI, NLP etc. Hays Specialist Recruitment Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying ...

users. Research team published at top AI venues with work adopted by leading universities and Fortune 500 R&D teams. Advisors include a leading NLP researcher and a Google DeepMind team lead. Flexibility. Fully remote, UK timezone. Regular offsites. We care about what you ship, not when you’re online. ...

users. Research team published at top AI venues with work adopted by leading universities and Fortune 500 R&D teams. Advisors include a leading NLP researcher and a Google DeepMind team lead. Flexibility. Fully remote, UK timezone. Regular offsites. We care about what you ship, not when you’re online. ...

relevant internships in machine learning, data engineering, or software engineering. You’ll contribute to designing, implementing, and deploying production-grade ML systems—ranging from NLP pipelines to model‐driven workflow automation. You’ll learn quickly, gain real ownership, and see your work make tangible business impact. What … willingness to learn quickly. Foundational skills Degree in a STEM field. PhD candidates: applied research involving ML, optimisation, simulation, statistics, numerical methods, NLP, or related areas. Bachelor’s/Master’s: 1–2 years of industry experience or relevant internships in ML, software engineering, or data engineering. Programming experience (especially ...