576 to 600 of 1,380 Natural Language Processing Jobs in the UK

large-scale data processing Proficiency in coding with C++ or Python Solid understanding of ML fundamentals, algorithms, and techniques, including supervised, unsupervised, and reinforcement learning, and experience in NLP, computer vision, and generative AI Preferred Qualifications Experience with generative models such as diffusion models, GANs, and transformers for various media formats, including prompt engineering, fine-tuning, and evaluation Knowledge … at scale and extend beyond web search. We seek versatile engineers with fresh ideas across various domains, including information retrieval, distributed computing, system design, networking, data storage, security, AI, NLP, UI, and mobile development. As a software engineer, you will work on critical projects with opportunities to switch teams and projects as our business evolves. The Domain Applied ML team More ❯

models to forecast admissions/discharges, optimising resources and reducing bottlenecks in emergency departments. Analysing health disparities across populations by socio-economic factors, geography, or access to care. Applying NLP to unstructured data (e.g., clinician notes, patient feedback) for insights into patient needs. Using machine learning to predict outcomes like readmission rates or disease progression, supporting proactive care. Developing econometric … like emergency departments. o Analysing disparities in health outcomes across different populations, identifying factors like socio-economic status, geography, or access to care that contribute to inequalities. o Applying NLP techniques to unstructured text data, such as clinician notes or patient feedback, to extract key information and improve understanding of patient needs and outcomes. o Using supervised and unsupervised machine … health, hospital utilisation, or treatment costs. · Analyse datasets to identify trends and patterns, and applies statistical models to solve business problems; make decisions on appropriate methods for data cleaning, processing, and analysis. · Follow data analysis and econometrics best practices and contribute to the ongoing development and improvement of these. · Be able to use, adapt and improve systems and software More ❯

of Gigabytes/tens of millions rows of data per day, Vaix is building a wide range of Machine Learning solutions, from Recommendation engines, human behavior predictive models, to Natural Language Processing. We process hundreds of API requests per second from operators and respond back with latency in milliseconds. Vaix is now looking to recruit an experienced & passionate … including MS Office, Figma, Miro, Jira, Slack, and others. KPI-driven with proven ability to query, analyze, and understand data using required analytical tools. Communication & Presentation Excellence: Strong English language skills (spoken and written), with additional languages as a plus. Ability to present business and technical concepts clearly across verbal, written, and presentation formats, including sales pitches and internal More ❯

re looking for candidates with strong experience in Computational Linguistics to help build and refine intelligent language technologies, combining linguistic expertise with technical skills to drive innovation in NLP and AI applications. Our client uses behavioural biometric interactions and advanced AI to create unique digital user identities, enabling seamless, intelligent security systems that adapt in real time. With ambitious More ❯

at multi-modal content understanding problems. Ideally you'd have: At least 1-3 years of model training, deployment and maintenance experience in a production environment Strong skills in NLP, LLMs and deep learning Solid background in algorithms, data structures, and object-oriented programming Experience working with a cloud technology stack (eg. AWS or GCP) and developing machine learning models … in Computer Science or a related field Nice to haves: Experience in dealing with large scale AI problems, ideally in the generative-AI field Demonstrated expertise in large vision-language models for diverse real-world applications, e.g. classification, detection, question-answering, etc. Published research in areas of machine learning at major conferences (NeurIPS, ICML, EMNLP, CVPR, etc.) and/ More ❯

and retrieval-augmented generation (RAG) pipelines. Experience designing and evaluating LLM-powered systems such as chatbots, summarization tools, content generation workflows, or intelligent data extraction pipelines. Deep understanding of NLP fundamentals: text preprocessing, language modeling, and semantic similarity. Strong proficiency in Python, including use of ML libraries such as TensorFlow, PyTorch, or similar. Experience with data science tools and More ❯

of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). Experience deploying ML models in production using REST APIs, microservices, and Docker containers. Understanding of NLP, LLMs, and prompt engineering techniques. Proficient in version control, CI/CD pipelines, and test-driven development. Nice to Have: Experience within financial services or fintech. Familiarity with MLOps tools … e.g., MLflow, Kubeflow, SageMaker). Understanding of regulatory or compliance frameworks. Academic background in mathematics, statistics, or quantitative disciplines. Who You Are: A natural problem-solver and independent thinker with a structured approach to work. Passionate about learning, growth, and continuous improvement. Organised and self-motivated, with excellent time management. Comfortable taking initiative and ownership of technical decisions. A More ❯

of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). Experience deploying ML models in production using REST APIs, microservices, and Docker containers. Understanding of NLP, LLMs, and prompt engineering techniques. Proficient in version control, CI/CD pipelines, and test-driven development. Nice to Have: Experience within financial services or fintech. Familiarity with MLOps tools … e.g., MLflow, Kubeflow, SageMaker). Understanding of regulatory or compliance frameworks. Academic background in mathematics, statistics, or quantitative disciplines. Who You Are: A natural problem-solver and independent thinker with a structured approach to work. Passionate about learning, growth, and continuous improvement. Organised and self-motivated, with excellent time management. Comfortable taking initiative and ownership of technical decisions. A More ❯

tackling advanced RAG or agentic use cases • You have deep understanding of concepts and algorithms underlying machine learning and LLMs • You're experienced with building and deploying LLMs or NLP applications • You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces. • You have strong technical coding skills in Python • You have … transformer-based models) and a broad knowledge of the field of AI • Publication record in AI or a related field • Strong interest in pre-training fine-tuning and using language models for applications • Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager Benefits We have local offices in Paris, London, Marseille and More ❯

Strong skills with ML frameworks (TensorFlow, PyTorch) and LLM tools (Hugging Face, LangChain, OpenAI APIs) Vector Understanding : Solid knowledge of embeddings, vector databases (Pinecone, Weaviate, FAISS), and RAG pipelines NLP Fundamentals : Text preprocessing, language modelling, and semantic similarity Cloud Experience : AWS ecosystem knowledge (SageMaker, Lambda, etc.) Production Ready : ETL pipelines, version control, Agile methodologies It would be a major More ❯

of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). Experience deploying ML models in production using REST APIs, microservices, and Docker containers. Understanding of NLP, LLMs, and prompt engineering techniques. Proficient in version control, CI/CD pipelines, and test-driven development. Nice to Have: Experience within financial services or fintech. Familiarity with MLOps tools … e.g., MLflow, Kubeflow, SageMaker). Understanding of regulatory or compliance frameworks. Academic background in mathematics, statistics, or quantitative disciplines. Who You Are: A natural problem-solver and independent thinker with a structured approach to work. Passionate about learning, growth, and continuous improvement. Organised and self-motivated, with excellent time management. Comfortable taking initiative and ownership of technical decisions. A More ❯

for an AI/ML scientist who has experience building, applying and customizing GenAI and traditional ML solutions to solve customer problems. Techniques we use on the team include NLP, supervised and unsupervised learning, recommendation systems, machine learning on graphs, reinforcement learning, algorithmic fairness and others on rich and novel datasets. As an applied scientist on the team, you will … measuring organizational north star metrics. BASIC QUALIFICATIONS - Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field - Experience programming in Java, C++, Python or related language - Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse PREFERRED QUALIFICATIONS - Experience implementing algorithms using both toolkits and self-developed code - Have publications at top-tier peer More ❯

clinical studies. Equitable Access: We are committed to ensuring that new cures are accessible to all patients. The Data Scientist at Every Cure will be critical in applying large language models (LLMs), transformers, and cutting-edge machine learning methodologies to support downstream validation in drug repurposing predictions. The Data Scientist will collaborate with data engineers, clinical scientists, tech translators … you'll make an impact - Advance Model Development: Design, develop, and deploy LLM-based models and algorithms to generate and validate drug repurposing predictions. Innovate: Apply transformers and advanced NLP techniques in the context of biomedical knowledge graphs and clinical data integration. Collaborate: Partner with clinical scientists, business leaders, and fellow data scientists to translate research challenges into scalable data More ❯

millions in business value. To be successful as a Data Scientist, you should have experience with: Commercial or academic experience in developing machine learning models (e.g., clustering, classification, regression, NLP). Comfortable working in Python and using key data science packages. Working knowledge of SQL. Ability to articulate technical findings in business terms and demonstrate value to stakeholders. Some other … have an impact on the work of related teams within the area. Partner with other functions and business areas. Takes responsibility for end results of a team’s operational processing and activities. Escalate breaches of policies/procedure appropriately. Take responsibility for embedding new policies/procedures adopted due to risk mitigation. Advise and influence decision making within own More ❯

data structures, algorithms, data modelling, and software architecture Solid understanding of classical Machine Learning algorithms (e.g., Logistic Regression, Random Forest, XGBoost, etc.), state-of-the-art research areas (e.g., NLP, Transfer Learning, etc.), and modern Deep Learning algorithms (e.g., BERT, LSTM, etc.) Solid knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib, etc.) Understanding … of model evaluation, data pre-processing techniques, such as standardisation, normalisation, and handling missing data Solid understanding of summary, robust, and nonparametric statistics; hypothesis testing; probability distributions; sampling techniques; and stochastic processes Core Behaviours Be Customer Focused: Constantly improving our customers' experience Be Human: Acting with humanity and care Be Curious: Thrive on learning, thinking beyond the obvious Be More ❯

with a statistical programming language (e.g., Python), applied machine learning techniques, and using OSS frameworks (e.g., TensorFlow, PyTorch). Building AI applications (e.g., deep learning, LLM/RAG, NLP, computer vision, or pattern recognition). Machine Learning Operations design, including: Previous successful experience in AI systems design, with the ability to architect and explain data pipelines, ML pipelines, and More ❯

an organisation that encourages continuous personal development, and are keen to talk with good candidate Desirable but not essential Demonstrable interest in Artificial Intelligence, Machine Learning, Deep Learning, or Natural Language Processing. Some hands-on experience with AI concepts, libraries, or frameworks (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers, Keras, etc.). Familiarity with Python for AI More ❯

Strong understanding of the theory of generative AI systems e.g., LLMs, RAG, Graph networks Strong experience deploying LLM’s for searching pipelines Up to date with current LLM and NLP research Experience designing, developing and deploying production machine learning pipelines Strong background in NLP techniques BS, MS or Ph.D. degree in Computer Science or related quantitative field Strong presentation skills More ❯

Strong understanding of the theory of generative AI systems e.g., LLMs, RAG, Graph networks Strong experience deploying LLM’s for searching pipelines Up to date with current LLM and NLP research Experience designing, developing and deploying production machine learning pipelines Strong background in NLP techniques BS, MS or Ph.D. degree in Computer Science or related quantitative field Strong presentation skills More ❯

metrics. Your Mission: Do More With Less You'll be instrumental in: Strategic Data Leadership: Architect and build product data infrastructure to transform review data into actionable merchant insights NLP/ML Development: Create models that analyse review content, identify trust patterns, and establish merchant benchmarks Pipeline Architecture: Build scalable systems that efficiently process our extensive review and merchant data … features and new products. What You'll Bring Must-Haves: 5+ years experience in data engineering and data science roles Strong programming skills in Python and SQL Experience building NLP/ML models, particularly for text classification or sentiment analysis Background in developing data pipelines and ETL processes Proven ability to translate complex data models into business insights Experience working More ❯

training and fine-tuning models, building robust, production-ready model inference pipelines, and conducting comprehensive exploratory data analysis and data enrichment. Key Responsibilities: Train, fine-tune, and enhance LLM & NLP models using the open-source Python library ecosystem. Experience with LLMs, Generative AI, and deep learning is a significant advantage. Build data science and data engineering pipelines specific to analyzing … biostatistics is highly beneficial. A PhD in a relevant field is but not required if exceptional experience is demonstrated. Experience with John Snow Labs’ technology stack, such as Spark NLP or the medical models, is a plus. What We Offer: A chance to work on cutting-edge problems in healthcare and life sciences, contributing to meaningful projects that impact patient More ❯

speaks fluent LLM and dreams in Vector Databases. As a Senior AI Engineer, you will be working with the latest in AI technology, including agent libraries, advanced LLMs and NLP tools. You'll have the opportunity and autonomy to lead the development and implementation of AI-powered solutions. This role will focus on integrating diverse data sources, refining AI interactions … to your family why you're "still playing with computers" (because the results speak for themselves) A day in the life of a Senior AI Integration Engineer Working with NLP that utilizes cutting-edge AI technologies to integrate AI-driven insights across company systems, enhancing access to data and supporting decision-making processes. Leverage AI technologies (LLMs) to continue development … connecting the dots What you’ll need to succeed: At least 3 years of proficiency in AI and machine learning technologies, particularly LLMs. Strong experience with prompt engineering and NLP tasks. Proven experience integrating AI systems with data platforms (databases, data lakes, APIs). Familiarity with data wrangling and preparation tools. Programming skill in Python and experience with AI frameworks More ❯

/QA Engineer, you need to be able to understand the product and client requirements so as to test the product in extreme scenarios and corner conditions. Knowledge in NLP, LLM, AI, and healthcare will help you understand the product better and in turn write better test cases and documentation. Key Responsibilities Performing best practices and software testing standards, defect …/CD and the setup of relevant pipeline and processes. Work experience with working in Linux and Microsoft Azure. Nice to Have Experience with deep learning, machine learning and NLP frameworks such as PyTorch, HuggingFace Transformer, Scikit-learn. Experience with multiple cloud platforms such as AWS, Google Cloud Platform, Oracle, NVIDIA, or on-prem environments. Perks and Benefits Salary dependent More ❯

engineering and data science team, which we’d like to expand with a full-time Python Developer. EntityX's technology uses a range of in-house and 3rd party NLP and AI techniques to merge all of the curated knowledge within Wikipedia with billions of daily data points about consumer media content consumption, to generate a deep understanding of consumers … ability to work effectively in a collaborative, fast-paced environment. Experience with Go or a willingness to learn it. Experience deploying and managing services in Kubernetes. Knowledge of LLMs, NLP, embeddings, and AI-driven technologies. Contributions to open-source projects or personal projects showcasing technical expertise. Experience working in a startup or small-team environment where adaptability is key. Understanding More ❯

our last resort, not our first instinct. You'll be instrumental in: Strategic Data Leadership : Architect and build product data infrastructure to transform review data into actionable merchant insights NLP/ML Development : Create models that analyse review content, identify trust patterns, and establish merchant benchmarks Pipeline Architecture : Build scalable systems that efficiently process our extensive review and merchant data … based on merchant feedback What You'll Bring Must-Haves 5+ years experience in data engineering and data science roles Strong programming skills in Python and SQL Experience building NLP/ML models, particularly for text classification or sentiment analysis Background in developing data pipelines and ETL processes Proven ability to translate complex data models into business insights Experience working More ❯