1 to 25 of 780 Natural Language Processing Jobs in London

pipelines (e.g., DevOps pipelines, Git actions). Knowledge of infrastructure as code (e.g., Terraform, ARM Template, Databricks Asset Bundles). Understanding of advanced machine learning techniques, including graph-based processing, computer vision, natural language processing, and simulation modeling. Experience with generative AI and LLMs, such as LLamaIndex and LangChain Understanding of MLOps or LLMOps. Familiarity with More ❯

is crucial to our mission of making the world safer by empowering the human mind with the right information at the right time. Scope of Work: Design and improve NLP models for text analysis, entity recognition, and relationship extraction from web content. Analyze data to identify patterns and insights that can enhance our platform's capabilities. Research and evaluate algorithms … insights to users and stakeholders. Apply responsible AI practices in all aspects of model development. Analyze model performance, diagnose issues, and recommend improvements. Research and evaluate emerging technologies in NLP, information retrieval, and ML. Document methodologies, model architectures, and experimental results. Mentor junior team members and contribute to the data science community of practice. Your Profile: Bachelor's or Master … data science libraries (NumPy, Pandas, scikit-learn). Experience with SQL for data querying and analysis. Solid understanding of machine learning algorithms, statistical methods, and predictive modeling. Experience with NLP techniques for text analysis, classification, and information extraction. Knowledge of deep learning frameworks such as PyTorch or TensorFlow. Experience with data visualization tools (Matplotlib, Seaborn, Plotly, or similar). Strong More ❯

product strategy. In this role, you will: Lead AI strategy and execution in a high-ambiguity environment. Build, train, and deploy state-of-the-art models (e.g., deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures). Design infrastructure for data ingestion, annotation, experimentation, model versioning, and monitoring. Collaborate closely with product, design, and DevOps to integrate … product strategy. In this role, you will: Lead AI strategy and execution in a high-ambiguity environment. Build, train, and deploy state-of-the-art models (e.g., deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures). Design infrastructure for data ingestion, annotation, experimentation, model versioning, and monitoring. Collaborate closely with product, design, and DevOps to integrate … stealth-mode or early-stage startup, ideally taking an AI product from 0 → 1. Background in a relevant domain (e.g., healthcare AI, autonomous systems, finance, robotics, computer vision, or NLP). Hands-on experience with large-scale language models (LLMs) and prompt engineering (e.g., GPT, BERT, T5 family). Familiarity with on-device or edge-AI deployments (e.g., TensorFlow More ❯

workflows for data collection, analysis and reporting. Data analysis Analyse data trends, patterns and anomalies using statistical techniques to derive meaningful insights. Model development and evaluation Utilise machine learning, NLP, Generative AI, and other advanced statistical methods to build predictive and descriptive models. Validate and refine models to ensure accuracy and reliability. Reporting A proven track record of advanced dashboard More ❯

and data science solutions. Ensure sharing best practices and learnings with other squad members. Lead and manage development and research projects focused on generative AI, deep learning, machine learning, NLP, and large language models. Design, develop, and deploy state-of-the-art machine learning models and algorithms that leverage deep learning and NLP techniques. Collaborate with cross-functional teams … MLEs to identify innovative machine learning and Gen AI solutions that leverage data to meet business goals. Stay up to date with the latest advancements in AI, machine learning, NLP, and large language models, and apply this knowledge to drive innovation within the organization. Mentor and provide guidance to junior data scientists and researchers, fostering a culture of continuous … Data Science, Machine Learning, or a related field. A minimum of 7 years of experience in data science, with a strong focus on generative AI, deep learning, machine learning, NLP, and large language models. Proven track record of developing and deploying successful deep learning and NLP models in real-world applications. Proficiency in programming languages such as Python, and More ❯

us is a desire to learn, a mastery of our discipline, strong mathematical and statistical skills, and software engineering prowess. We typically specialise in fields such as Computer Vision, Natural Language Processing and Deep Learning. Our Data Scientists are responsible for all aspects of the AI lifecycle, from understanding business problems, preparing training data, designing and building … You write production-grade, scalable Python code, ensuring that your models are robust, maintainable, and optimised for performance Comfortable with PyTorch Knowledge of Transformer-based models Knowledge of Large Language Models (LLMs) Proven experience of having delivered successful Computer Vision or LLM projects into production Strong understanding of software development fundamentals, in particular deploying models to production and how … to set up pipelines Demonstrate expertise in deep learning for computer vision, natural language processing, reinforcement learning etc Displays in depth knowledge in machine learning best practices, scalable training and deployment, model introspection and evaluation Strong fundamentals in Mathematics, Statistics and Data Analysis Experience working in an Agile environment and knowledge of how Agile methodologies can be More ❯

business challenges and opportunities for AI-driven solutions. Design, develop, and deploy AI models and algorithms tailored to client needs. Provide technical expertise in AI technologies, including machine learning, natural language processing, and computer vision. Conduct data analysis and pre-processing to prepare datasets for AI model training. Implement AI models into production environments and optimize More ❯

capabilities to learn, reason and make decisions autonomously. Key Responsibilities: AI Systems Architecture: Design and develop the architecture and infrastructure for Gen AI systems, including mechanisms for data storage, processing, and retrieval. Ensure the system's scalability, flexibility, and efficiency to handle large algorithms. Algorithm Development: Develop and implement advanced AI algorithms and models, including machine learning, deep learning … effectiveness of trained models. Fine-tune models based on feedback and data insights. Neural Network Design: Design and optimize deep learning neural networks for various AI tasks, such as natural language processing, computer vision, recommendation systems, and predictive analytics. Implement innovative architectures and techniques to improve model accuracy and efficiency. System Integration: Collaborate with software developers and … technical and non-technical audiences. Mandatory Qualifications/Skills: A bachelor's or master's degree or equivalent in computer science, Artificial Intelligence, or related field. Experience with large language models (LLMs) and prompt engineering. Experience in designing and developing AI systems, including machine learning, deep learning, and neural networks. Strong programming skills in languages such as Python, R More ❯

to identify business challenges and opportunities for AI solutions. Design and develop AI models and algorithms to address client needs. Provide technical expertise in AI technologies, including machine learning, natural language processing, and computer vision. Conduct data analysis and preprocessing to prepare datasets for AI model training. Proven experience in data science and analytics, with a strong More ❯

be doing AI-Ready Data Development: Design, develop, and maintain high-quality AI-ready datasets, ensuring data integrity, usability, and scalability to support advanced Generative AI models. Advanced Data Processing: Lead hands-on efforts in complex data extraction, cleansing, and curation for diverse text and numerical datasets. Implement sophisticated metadata enrichment strategies to enhance data utility and accessibility for … AI systems. Algorithm Implementation & Optimization: Implement and optimize state-of-the-art algorithms and pipelines for efficient data processing, feature engineering, and data transformation tailored for LLM and GenAI applications. GenAI Application Development: Apply and integrate frameworks like LangChain and Hugging Face Transformers to build modular, scalable, and robust Generative AI data pipelines and applications. Prompt Engineering Application: Apply … engineering. Skills and Experience Academic Background: Advanced degree in AI, statistics, mathematics, computer science, or a related field. Programming and Frameworks: Deep experience with Python, TensorFlow or PyTorch, and NLP libraries such as spaCy and Hugging Face. GenAI Tools: Practical experience with LangChain, Hugging Face Transformers, and embedding models for building GenAI applications. Prompt Engineering: Deep expertise in prompt engineering More ❯

tune models for regression, classification, clustering, and deep learning. Explore and implement state-of-the-art AI approaches such as transformer models, generative AI, and reinforcement learning. Expertise in natural language processing to analyze and generate insights from unstructured text data. Advanced Analytics and Insights Extract actionable insights from structured and unstructured datasets to support strategic decision More ❯

and understanding of recent trends in Generative AI and LLMs. Experience in working with GenAI stack will be treated as strong credentials. Strong understanding of various machine learning and natural language processing technologies, such as classification, information retrieval, clustering, knowledge graph, semi-supervised learning and ranking. Excellent exploratory data analysis skills with the ability to slice and More ❯

in Python and its standard coding practices and common libraries. Experience with ML models and knowledge of at least one ML framework (PyTorch preferred). Experience in data pre-processing techniques, feature engineering, and model evaluation metrics. Proven … ability to manipulate, query and visualise data and training/evaluation results (using e.g., Pandas, Matplotlib, Seaborn). Proven understanding of Information Extraction and Retrieval techniques. Proven understanding of NLP and large language models. Proven understanding of database concepts (differences between graph/relational/non-relational). Proven familiarity with cloud computing platforms (e.g., AWS, Azure, GCP), Azure More ❯

Expertise in Machine Learning:*** Proficient in both supervised and unsupervised learning.* Techniques: Linear and logistic regressions, random forests, gradient boosting, neural networks (RNN, LSTM, CNN), text mining, topic extraction, NLP, K-Means, decision trees.* Applications: Computer vision, Generative AI, Language Models (e.g., GPT), Retrieval-Augmented Generation (RAG).**Technical Skills:*** Deep knowledge of Python (including libraries such as scikit … Jupyter, Spark/Scala or R, PostgreSQL, and ELK stack.* Proficiency in Java, Kubernetes, Docker, and microservices-oriented architecture.* Familiarity with MLOps practices and collaborative tools (e.g., GitLab).**Language Skills:*** English fluency (both written and verbal) is mandatory.Nokia is committed to innovation and technology leadership across mobile, fixed and cloud networks. Your career here will have a positive More ❯

strategies and maximize their marketing towards optimal growth. In this role, you will be responsible for combining these otherwise disconnected datasets, and with the help of advanced machine learning, NLP & Computer Vision techniques, help uncover new consumer insights allowing our clients to gain knowledge and insights on consumer behaviour. You will play a key role in standardizing our AI into … of some recognised AI and software leaders. · Experience in working with large datasets (> 1TB) · Able to implement production level coding practices, including unit testing and documentation · Proven experience building NLP & Computer Vision products with an engaged customer base · Experience researching and implementing latest scientific literature on NLP/CV and ML · Experience building prototypes and experiments to validate technical ideas … Extensive knowledge of open-source NLP & CV libraries · Skilled at explaining the technical subject matter to non-technical audiences (in English) · Nice to have: Experience working on an agile software engineering team and working directly with Product Management teams; Azure Databricks, Microsoft Azure certification, Azure AI Fundamentals, Azure Data Scientist Associate Preferred Skills/Experience: · Demonstrates strong interpersonal, communication, and More ❯

strategies and maximize their marketing towards optimal growth. In this role, you will be responsible for combining these otherwise disconnected datasets, and with the help of advanced machine learning, NLP & Computer Vision techniques, help uncover new consumer insights allowing our clients to gain knowledge and insights on consumer behaviour. You will play a key role in standardizing our AI into … of some recognised AI and software leaders. · Experience in working with large datasets (> 1TB) · Able to implement production level coding practices, including unit testing and documentation · Proven experience building NLP & Computer Vision products with an engaged customer base · Experience researching and implementing latest scientific literature on NLP/CV and ML · Experience building prototypes and experiments to validate technical ideas … Extensive knowledge of open-source NLP & CV libraries · Skilled at explaining the technical subject matter to non-technical audiences (in English) · Nice to have: Experience working on an agile software engineering team and working directly with Product Management teams; Azure Databricks, Microsoft Azure certification, Azure AI Fundamentals, Azure Data Scientist Associate Preferred Skills/Experience: · Demonstrates strong interpersonal, communication, and More ❯

strategies and maximize their marketing towards optimal growth. In this role, you will be responsible for combining these otherwise disconnected datasets, and with the help of advanced machine learning, NLP & Computer Vision techniques, help uncover new consumer insights allowing our clients to gain knowledge and insights on consumer behaviour. You will play a key role in standardizing our AI into … of some recognised AI and software leaders. · Experience in working with large datasets (> 1TB) · Able to implement production level coding practices, including unit testing and documentation · Proven experience building NLP & Computer Vision products with an engaged customer base · Experience researching and implementing latest scientific literature on NLP/CV and ML · Experience building prototypes and experiments to validate technical ideas … Extensive knowledge of open-source NLP & CV libraries · Skilled at explaining the technical subject matter to non-technical audiences (in English) · Nice to have: Experience working on an agile software engineering team and working directly with Product Management teams; Azure Databricks, Microsoft Azure certification, Azure AI Fundamentals, Azure Data Scientist Associate Preferred Skills/Experience: · Demonstrates strong interpersonal, communication, and More ❯

Scikit-learn, Hugging Face Transformers) Familiarity with embedding models, vector databases (e.g., Pinecone, FAISS, Weaviate) Experience with cloud platforms (AWS, GCP, or Azure) and MLOps pipelines Solid understanding of NLP, LLM fine-tuning, and prompt engineering Preferred Qualifications Familiarity with customer analytics and marketing automation workflows Experience in financial compliance (e.g., GDPR, FCA) or savings product optimization Knowledge of business More ❯

on experience in developing and implementing AI and Data cloud solutions. Experience working with Azure AI services (or AWS, GCP) and AI model deployment. Understanding of generative AI, LLMs, NLP, and machine learning frameworks (TensorFlow, PyTorch, Hugging Face, etc.). Understanding of the AI application lifecycle, including application prototyping, productionising and monitoring. Python/Go/R. Problem solving skills. More ❯

or applied AI solutions. • A passion for Generative AI, and an understanding of strengths and weaknesses of Generative LLM's • Fundamental knowledge of ML, and basic knowledge of AI, NLP, and Large Language Models (LLM) • Comfortable working with Python and Jupyter Notebooks • Should have in-depth knowledge and familiarity with cloud platforms like Amazon Web Services (AWS), Google Cloud … Platform (GCP), and Microsoft Azure. Technical Skills – Good to have: • Expertise in any one framework (TensorFlow, Pytorch, Keras) • Experience in a statistical programming language (e.g. R or Python) and applied machine learning and AI techniques (i.e computer vision, deep learning, conversational AI, and natural language processing frameworks.) • Experience with Transforms Architecture Design, specializing LLM (Zero/… in conversational system architecture • Extensive knowledge on API’s & Integrations, Patterns. • Extensive knowledge of big data technologies • Knowledge on Statistical Methods • OTHER SKILLS WE'D APPRECIATE 1. Understanding of NLP engines, Artificial Intelligence, Machine Learning frameworks etc. EDUCATION QUALIFICATION • Graduate in Engineering OR master’s in computer applications. Process Skills: • General SDLC processes • Understanding of utilizing Agile and Scrum software More ❯

new insights, enable analytics, gain efficiencies and automation. This role is based in an AI/ML team that is already working on projects involving Generative AI, Information Retrieval, NLP/NER/RE, document classification and data science, and has won awards and recognition for its work. The team's future projects will be in diverse areas, such as … 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 NLP: Named Entity Recognition across a variety of unstructured data. Evaluating and training BERT-like models such as GLiNER, NuNER for NER tasks. Analysing trade-offs between these models and LLMs … for NLP tasks. Relationship Extraction: Evaluating different models for use-case specific RE, such as ATG. Document and text Classification Data Science: Data clustering algorithms, feature engineering Evaluate and integrate new technologies and models. Cross-team collaboration, identifying innovations and architecting solutions. Provide leadership and technical direction to various business units and partners Why you? Qualifications & Skills: We are looking More ❯

and machine learning algorithms for Supervised and Unsupervised Learning, like Regression, Classification, Clustering, Dimensionality Reduction, Association Rules, Ranking, and Recommender Systems. Experience with Natural Language Processing (NLP and NLU). Experience using Generative AI systems (e.g. ChatGPT) and best practices (e.g. Prompt Engineering). Understanding the key concepts on how to apply Generative AI in building RAG … within a collaborative team environment. Desired Qualifications: Masters or PhD in Machine Learning/Data Mining/Statistics. Experience in building advanced Information Retrieval or Question Answering systems using NLP and Generative AI techniques (e.g. RAG and GraphRAG). Experience with construction and integration of Knowledge Graphs. Collaboration is our superpower, diversity unites us, and excellence is our standard. We More ❯

Problem-Solving Skills. Attention to Detail. Adaptability and Communication Skills. Patience and Persistence. Experience with advanced machine learning techniques such as deep learning, natural language processing (NLP), or reinforcement learning. Experience in using advanced features of cloud platforms (AWS, Azure, Google Cloud) such as machine learning services and automated data pipeline tools. Familiarity with big data frameworks More ❯

businesses. Each project is different - one week, you might solve a data engineering challenge, which could involve mining large datasets. The next week, you may find yourself working on natural language processing using large language models, developing innovative AI applications. Contribute to cutting-edge research projects, advancing Compass Lexecon’s thought leadership in the application of … SQL and NoSQL databases (e.g. MongoDB) and Deep understanding and hands-on experience with a variety of data science tools and concepts, such as machine learning, causal inference, optimisation, natural language processing and computer vision Experience with cloud computing platforms (Azure, AWS, GCP) and containerization (Docker) Knowledge of data engineering principles such as data modelling, ETL processes More ❯

a Data Scientist, this role plays a crucial role in delivering the generative artificial intelligence (GenAI) solutions for our clients. This position requires a deep understanding of machine learning, natural language processing, and generative models, combined with problem-solving skills and a passion for innovation. Possessing a deep understanding of AWS products and services, as a Delivery … through our global specialty practices, which cover a variety of solutions, technologies, and industries. Key job responsibilities 1. Generative AI Model Development: -Design and develop generative AI models, including language models, image generation models, and multimodal models. -Explore and implement advanced techniques in areas such as transformer architectures, attention mechanisms, and self-supervised learning. -Conduct research and stay up … learning models, with a strong focus on generative AI techniques. - Proficiency in programming languages such as Python, PyTorch, or TensorFlow, and experience with deep learning frameworks. - Strong background in natural language processing, computer vision, or multimodal learning. - Ability to communicate technical concepts to both technical and non-technical audiences. PREFERRED QUALIFICATIONS - Experience with large language models More ❯