51 to 75 of 105 Natural Language Processing Jobs in England

collaborate closely with Engineering and Product teams to bring ideas to life. Apply advanced machine learning and LLM techniques, including RAG, agents and NLP, where they drive meaningful customer and product impact. Work with large-scale datasets in cloud environments to deliver robust, scalable systems. Contribute to product strategy through ...

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 ...

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. ...

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 … requirement specifications Establish best practices and reusable design patterns Your ProfileEssential Skills/Knowledge/ExperienceData 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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

documentation, and delivery in a DevOps context. Apply a deep understanding of ML techniques, from supervised/unsupervised learning to generative AI and large language models. What We’re Looking For Essential Skills and Experience: Proven ability to solve complex, real-world problems through data science and analytics. Experience … explaining complex topics to non-technical stakeholders. Ability to align data science efforts with broader business objectives. Desirable Skills: Experience using R and NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ...

line manager to plan for functional spend. Ensuring accuracy of financial claims for self and staff. Performance and effective analytical model cost and data processing Please see Job Description Person Specification Pspec Essential oDesigning algorithms for actionable outcomes oStrong proficiency in SQL, R, Python, and tools like Alteryx, TensorFlow … various data sources can be used to identify fraudulent activity. Advanced knowledge and practical experience of developing, implementing and harnessing generative AI and NLP for the benefit of counter fraud. oAccredited Counter Fraud Specialist or member of Government Counter fraud Profession oDemonstrate CPD. oPolitically astute with knowledge of national ...

line manager to plan for functional spend. Ensuring accuracy of financial claims for self and staff. Performance and effective analytical model cost and data processing Please see Job Description Person Specification Pspec Essential oDesigning algorithms for actionable outcomes oStrong proficiency in SQL, R, Python, and tools like Alteryx, TensorFlow … various data sources can be used to identify fraudulent activity. Advanced knowledge and practical experience of developing, implementing and harnessing generative AI and NLP for the benefit of counter fraud. oAccredited Counter Fraud Specialist or member of Government Counter fraud Profession oDemonstrate CPD. oPolitically astute with knowledge of national ...

engineering experience Python and ML frameworks Experience deploying models to production Financial services or data-heavy background Cloud ML tooling exposure Nice to Have NLP or time-series modelling MLOps experience Risk or fraud use cases Why Join Applied ML in production High-impact financial use cases Growing AI capability ...

experience we consider to 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). AI-driven SDLC: Claude Code, Codex. Experience using Cursor, Windsurf, Replit, and GitHub Copilot. Google Stitch. ...

Skills & Experience Proven experience delivering AI, automation, or digital transformation programmes Strong understanding of AI/ML and intelligent automation technologies (e.g. RPA, NLP) Excellent stakeholder management and communication skills Experience working in Agile delivery environments Ability to bridge the gap between technical teams and business leaders Clearance Active ...

Things that would be great but aren't required: Experience with LLM APIs, RAG systems, vector databases Background in conversational UI, voice interfaces, or NLP Understanding of qualitative research or data visualisation Why Join Lichen AI? Shape the technical direction of a mission-driven company with the opportunity to grow ...

agile product development environments. Desirable Experience working in regulated environments or with legal workflows. Thorough understanding of AI technologies used in legal environments (LLMs, NLP, extraction/classification models, summarisation, RAG pipelines, etc.) Hybrid Working Birketts is a flexible business which has embraced a hybrid working model where our colleagues ...