1 to 25 of 352 Natural Language Processing Jobs

technology sector Salary up to £130k + Equity Paddington based (4-5 days per week in-office) Tech environment: Python | PyTorch | TensorFlow | scikit-learn | NLP | LLMs | Data Engineering If you wish to keep your CV/data private, feel free to WhatsApp your details/… Design, develop, and deploy end-to-end ML systems , from concept to production. Build models for intelligent automation, natural language processing (NLP), and data-driven insights. Work with Python , PyTorch , TensorFlow , and scikit-learn to prototype and scale solutions. Partner with senior leadership to define

time and resources to explore, learn, and publish. What We’re Looking For 0–3 years of experience in Machine Learning, Data Science, or NLP/LLM. Strong Python skills; exposure to PyTorch/TensorFlow/Hugging Face. (Bonus) understand fundamentals of deep learning, LLMs, and MLOps, vector databases, embeddings … join an early-stage company where their work genuinely moves the needle. Machine Learning Engineer, LLM Engineer, AI Engineer, Artificial Intelligence, Deep Learning, NLP, Natural Language Processing, Large Language Models, Generative AI, GenAI, Neural Networks, PyTorch, TensorFlow, Hugging Face, OpenAI, LangChain, RAG, Retrieval-Augmented Generation, Python

handling, and writing clean, maintainable code. Experience with key libraries including Pandas, NumPy for data manipulation, requests and APIs for integrations, asyncio for concurrent processing, and building robust automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep expertise in AI/… frameworks including TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering, and MLOps practices for production deployment. Generative AI & LLM Integration - Proficient in working with Large Language

handling, and writing clean, maintainable code. Experience with key libraries including Pandas, NumPy for data manipulation, requests and APIs for integrations, asyncio for concurrent processing, and building robust automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep expertise in AI/… frameworks including TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering, and MLOps practices for production deployment. Generative AI & LLM Integration - Proficient in working with Large Language

Expertise in AI/ML technologies (e.g., TensorFlow, PyTorch, Scikit-learn, Keras) and understanding of deep learning and natural language processing (NLP). • Strong understanding of big data platforms such as Hadoop, Apache Spark, and data lakes. • Hands-on experience with cloud platforms (Azure, AWS, or Google

/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning, natural language processing (NLP), and statistical modelling to extract insights and drive decision-making. Explore and evaluate Generative AI applications, including prompt engineering, fine-tuning, and safety alignment using tools like

/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning, natural language processing (NLP), and statistical modelling to extract insights and drive decision-making. Explore and evaluate Generative AI applications, including prompt engineering, fine-tuning, and safety alignment using tools like

/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning, natural language processing (NLP), and statistical modelling to extract insights and drive decision-making. Explore and evaluate Generative AI applications, including prompt engineering, fine-tuning, and safety alignment using tools like

/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning, natural language processing (NLP), and statistical modelling to extract insights and drive decision-making. Explore and evaluate Generative AI applications, including prompt engineering, fine-tuning, and safety alignment using tools like

/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning, natural language processing (NLP), and statistical modelling to extract insights and drive decision-making. Explore and evaluate Generative AI applications, including prompt engineering, fine-tuning, and safety alignment using tools like

/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning, natural language processing (NLP), and statistical modelling to extract insights and drive decision-making. Explore and evaluate Generative AI applications, including prompt engineering, fine-tuning, and safety alignment using tools like

/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning, natural language processing (NLP), and statistical modelling to extract insights and drive decision-making. Explore and evaluate Generative AI applications, including prompt engineering, fine-tuning, and safety alignment using tools like

/CD tooling to ensure seamless model delivery and monitoring. Apply advanced techniques in deep learning, natural language processing (NLP), and statistical modelling to extract insights and drive decision-making. Explore and evaluate Generative AI applications, including prompt engineering, fine-tuning, and safety alignment using tools like

domains Serve as the trusted technical advisor for customers developing GenAI solutions, such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, content generation, and monitoring What We Look For 5+ years of experience in a customer-facing technical role. Pre-sales or post …/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring Data Scientist: Experience with the latest techniques in natural language processing including vector databases, fine-tuning LLMs, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI Graduate degree

methods like confidence intervals, point estimates and sample size estimates to make sound and confident inferences on data and A/B tests Applying Natural Language models to Google keyword analysis and applying meta models to our multi-objective ranking problem Communicating complex analytical topics in a clean … location if outside commuting distance Preferred Experience Helpful to understand ML techniques like Regression, Naïve Bayes, Gradient Boosting, Random Forests, SVMs, Neural Networks, and NLP Helpful to have experience with programming, statistical, and querying languages like Python, R, SQL/Hive, Java Helpful to understand distributed file systems, scalable datastores

Learning Model training/explanation, bias detection, evaluation metric analysis Deep Learning Neural net architecture design, backpropagation walkthroughs Natural Language Processing (NLP) Text classification, summarization, sentiment analysis Computer Vision Image labeling, object detection, image captioning MLOps/Deployment Model lifecycle support, pipeline design, monitoring/rollback flows

Neo4J...) Data exchange and processing skills (e.g. ETL, ESB, API...) Development (e.g. Python) skills Big data technologies knowledge (e.g. Hadoop stack) Knowledge in NLP (Natural Language Processing) Knowledge in OCR (Object Character Recognition) Knowledge in Generative AI (Artificial Intelligence) would be advantageous Experience in containerisation technologies

Neo4J...) Data exchange and processing skills (e.g. ETL, ESB, API...) Development (e.g. Python) skills Big data technologies knowledge (e.g. Hadoop stack) Knowledge in NLP (Natural Language Processing) Knowledge in OCR (Object Character Recognition) Knowledge in Generative AI (Artificial Intelligence) would be advantageous Experience in containerisation technologies

Neo4J...) Data exchange and processing skills (e.g. ETL, ESB, API...) Development (e.g. Python) skills Big data technologies knowledge (e.g. Hadoop stack) Knowledge in NLP (Natural Language Processing) Knowledge in OCR (Object Character Recognition) Knowledge in Generative AI (Artificial Intelligence) would be advantageous Experience in containerisation technologies

120k total compensation About Us We’re an ambitious technology company using advanced Machine Learning (ML) and Natural Language Processing (NLP) to power next-generation products. Until now, our AI projects have relied on third-party engines deployed via Docker — but it’s time to take … Infrastructure Lead — someone with the technical depth and vision to architect, implement, and scale an environment capable of supporting multiple ML and NLP initiatives across the business. The Role As our first senior AI hire, you’ll take ownership of designing and building the foundation of our AI ecosystem.

alongside an appreciation for regulatory considerations unique to this sector. You possess a thorough understanding of artificial intelligence concepts such as machine learning or NLP without needing direct coding skills-enabling you to communicate effectively with technical experts while focusing on strategic outcomes. Your proven ability in programme management means … well as familiarity with regulatory frameworks governing financial institutions. Conversant in artificial intelligence concepts such as machine learning, natural language processing (NLP), automation technologies including generative AI or agentic AI-without requiring hands-on coding expertise. Extensive experience in programme management encompassing oversight of multiple concurrent workstreams

collaborate closely with a multi-disciplined and distributed work function, utilise machine/deep learning and Natural Language Processing (NLP) to integrate AI solutions into products and services. Key skills and experience required: Hands-on AI and ML Engineering experience Experience developing in Python

collaborate closely with a multi-disciplined and distributed work function, utilise machine/deep learning and Natural Language Processing (NLP) to integrate AI solutions into products and services. Key skills and experience required: Hands-on AI and ML Engineering experience Experience developing in Python

We are hiring motivated individuals for a flexible 100% remote role that involves supporting day-to-day tasks, ensuring smooth

company is building a next-generation platform that helps professionals extract insights and automate workflows across large document sets. Their product combines structured data, natural-language processing, and workflow automation to help users make faster, higher-quality decisions. They're backed by leading European and US investors … Interest in AI-enabled products or automation platforms. Nice to Have Experience leading small engineering teams or mentoring others. Familiarity with document processing, NLP, or knowledge-graph-style systems. Previous exposure to enterprise integrations or SaaS products. Comfort working with cloud-native infrastructure (e.g. AWS, GCP, Docker).