251 to 275 of 360 Natural Language Processing Jobs in England

Project Manager, you need to be able to understand the product and client requirements so as to bridge the communication between the clients and the technical team. Knowledge in NLP, AI and biomedicine will help you understand the product and client requirement better. Key technical responsibilities: Understand the clients in life sciences (such as biopharmaceutical companies and healthcare providers) they More ❯

z2bz0 years of experience in AI, ML, or Health Tech R&D , with a strong focus on clinical impact and product delivery Direct experience with conversational AI, LLMs, NLP , and applied machine learning in health-related contexts Understanding of mental health clinical pathways , triage models, and digital therapeutics Strong knowledge of regulatory requirements and risk management in digital health (e.g. More ❯

projects working alongside high-performing ML, data, and software engineers using agile software development Demonstrable ML proficiency with a deep understanding of how to utilize state-of-the-art NLP and ML techniques Mastery of several ML frameworks and libraries, with the ability to architect complex ML systems from scratch Extensive experience with Python and PyTorch Track record of contributing … development lifecycle from architecture and technical design, through data collection and preparation, model selection, training, fine-tuning and evaluation, to deployment and maintenance Familiarity with implementing solutions leveraging Large Language Models, as well as a deep understanding of how to implement solutions using Retrieval Augmented Generation (RAG) architecture Experience with graph machine learning (i.e. graph neural networks, graph data … eye for details such as scalability and performance of a potential solution Comprehensive knowledge of software engineering, programming fundamentals and industry experience using Python Experience with data manipulation and processing, such as SQL, Cypher or Pandas A can-do proactive and assertive attitude - your manager believes in freedom and responsibility and helping you own what you do; you will More ❯

of our Corporate and Investment Banking (CIB) business. We are looking for a senior data scientist with expertise in both classical machine learning and the latest advancements in Large Language Models (LLMs) to help shape the future of financial services. Responsibilities Collaborate with product owners and business stakeholders to identify pain points, define use cases, and translate business needs … and regulatory requirements. Work closely with MLOps engineers and the wider Tech and Data teams to deploy production-ready solutions. Stay ahead of industry trends, particularly in Data Science, NLP, and GenAi advancements, and share insights across the team. Ensure data quality and governance standards are maintained across all AI and analytics projects. Support risk and audit management for AI … and ensuring compliance with regulatory frameworks. Skills and Qualifications Skills & Expertise Strong experience in machine learning, deep learning, and statistical analysis. Expertise in Python, with proficiency in ML and NLP libraries such as Scikit-learn, TensorFlow, Faiss, LangChain, Transformers and PyTorch. Experience with big data tools such as Hadoop, Spark, and Hive. Familiarity with CI/CD and MLOps frameworks More ❯

Key Responsibilities: 10+yrs of experience in design, develop, and deploy AI/ML models and solutions using Python or any other competitive scripting languages Build and fine-tune large language models (LLMs) and Generative AI systems. Integrate AI solutions with OpenAI services through Microsoft Azure. Expert or advanced-level expertise in at least one leading LLM that is competitive … Proficiency in Python and machine learning framework s (e.g., TensorFlow, PyTorch, Scikit-Learn). Hands-on experience with OpenAI APIs and Microsoft Azure AI services. Strong understanding of large language models, prompt engineering, and fine-tuning techniques. Experience with data manipulation libraries (e.g., Pandas, NumPy) and cloud platforms. Familiarity with MLOps … version control (e.g., Git), and deployment tools (e.g., Docker, Kubernetes). Excellent problem-solving skills and the ability to work on complex AI challenges. Nice to Have: Experience with NLP frameworks, transformer architectures, and Hugging Face libraries. Knowledge of AI ethics, data privacy, and model interpretability. Previous experience working on AI-based translation, automation, or localization projects. Roadmap for Success More ❯

high standards in code review, 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 coaching and reviewing work of … services. Strong communication skills, capable of 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 ML services, Docker, Kubernetes. Exposure More ❯

high standards in code review, 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 coaching and reviewing work of … services. Strong communication skills, capable of 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 ML services, Docker, Kubernetes. Exposure More ❯

learning algorithm that determines the most effective actions for each customer, enhancing results and minimising unwanted interactions OphelosGPT - our generative AI model for empathetic, context-aware customer communication Advanced NLP & LLM-driven classifiers to identify vulnerable customers, disputes, and intent, enabling proactive support and accurate resolutions Forecasting and risk models to improve decision-making and operational efficiency As part of … which include setting up and conducting interviews and tests for applicants, evaluating and assessing the results thereto, and as is otherwise needed in the recruitment and hiring processes. Such processing is legally permissible under Art. 6(1)(f) of Regulation (EU) 2016/679 (General Data Protection Regulation) as necessary for the purposes of the legitimate interests pursued by … employment. Under the GDPR, you have the right to request access to your personal data, to request that your personal data be rectified or erased, and to request that processing of your personal data be restricted. You also have to right to data portability. In addition, you may lodge a complaint with an EU supervisory authority. Create a Job More ❯

engineering principles, Agile methodologies, and responsible AI practices throughout the solution lifecycle. Stay Current: Maintain deep expertise in the latest trends, research, tools, and technologies within Generative AI, Large Language Models (LLMs), and Agentic AI paradigms. Practice Development: Support the expansion of the GenAI practice by defining delivery playbooks, reusable assets, talent strategies, and mentoring early-stage architects and … Agentic AI opportunities. Qualifications and 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). LLM Expertise: Proven experience developing applications leveraging state-of-the-art LLMs (e.g., GPT series, Llama series, Mistral, Claude) including prompt engineering More ❯

AI/ML can unlock insights and improve decision-making. Perform advanced analysis on large, complex datasets using statistical and modelling techniques. Build, test, and tune ML models (especially NLP or computer vision) using Python and modern ML libraries, all within Google Cloud Platform (GCP) . Optimise models for accuracy and performance, ready for product integration. Stay up-to-date … stakeholders. Ensure your workflows are reproducible and well-documented, including experiment tracking and model lineage. What You'll Bring: 3+ years' experience building and deploying ML models, ideally in NLP or computer vision domains. Expert-level Python and SQL, with solid experience using libraries like Pandas, Scikit-Learn, TensorFlow, etc. Proven experience working with BigQuery and big data pipelines on More ❯

/Data Science Preferred: Experience with Big Data/Data Science technology Level of experience (years): Entry Level (Less than 2 years of Experience) How to apply: Please mention NLP People as a source when applying Tagged as: Big Data , Data Mining , Data Warehouse , Industry , United Kingdom More ❯

Contribute to quantitative data analyses in STATA Company: King's College London Qualifications: N/A Specific requirements: Fixed term contract for 12 months. How to apply: Please mention NLP People as a source when applying Tagged as: Academia , Big Data , Data Analysis , Data Mining , United Kingdom More ❯

in ambiguous problem spaces, and mentor junior team members Strong collaboration and communication skills, with experience aligning technical approaches with cross-functional teams and stakeholders Bonus Points Experience with NLP, image classifiers, deep learning, or large language models Experience with experiment design and conducting A/B tests Experience building shared or platform-style ML systems Experience with Databricks More ❯

in ambiguous problem spaces, and mentor junior team members Strong collaboration and communication skills, with experience aligning technical approaches with cross-functional teams and stakeholders Bonus Points Experience with NLP, image classifiers, deep learning, or large language models Experience with experiment design and conducting A/B tests Experience building shared or platform-style ML systems Experience with Databricks More ❯

As a Machine Learning Engineer at Trainline you will... Work in cross-functional teams combining data scientists, software, data and machine learning engineers, and product managers Design and deliver NLP based machine learning systems at scale that drive measurable impact for our business Own the full end to end machine learning delivery lifecycle including data exploration, feature engineering, model selection … of rigorous learning and experimentation We'd love to hear from you if you... Have an advanced degree in Computer Science, Mathematics or a similar quantitative discipline Understanding of NLP algorithms and techniquesand/or experience with Large Language Models (fine tuning, RAG, agents) Are proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc. More ❯

As a Machine Learning Engineer at Trainline you will Work in cross-functional teams combining data scientists, software, data and machine learning engineers, and product managers Design and deliver NLP based machine learning systems at scale that drive measurable impact for our business Own the full end to end machine learning delivery lifecycle including data exploration, feature engineering, model selection … of rigorous learning and experimentation We'd love to hear from you if you Have an advanced degree in Computer Science, Mathematics or a similar quantitative discipline Understanding of NLP algorithms and techniquesand/or experience with Large Language Models (fine tuning, RAG, agents) Are proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc. More ❯

An early-career technologist looking to gain a formal qualification while working on meaningful, real-world applications. Required skills: Solid foundation in AI/ML principles (e.g. neural networks, NLP, transformers, speech processing). Hands-on experience with Python and popular ML frameworks (e.g. PyTorch, TensorFlow, Hugging Face). Familiarity with LLM APIs and open-source models (e.g. GPT More ❯

are not expected to be experienced in all areas listed below. AI techniques (supervised and unsupervised machine learning, deep learning, graph data analytics, statistical analysis, time series, geospatial analysis, NLP, sentiment analysis, pattern detection, etc.) Python, R, or Spark for data insights Data Bricks/Data QISQL for data access and processing (PostgreSQL preferred, but general SQL knowledge is More ❯

trained models. As a Research Scientist Manager, you will play a key part in leading a diverse global team of experts. We hire world-leading specialists in ML/NLP/GenAI, as well as Engineering, to drive the company's leading internal AI model development. You will have the opportunity to publish your research findings as well as contribute … re a fit for the role if your background includes: Required qualifications : PhD in a relevant discipline. 3+ years of hands-on experience leading teams building advanced ML/NLP/AI systems in academia (e.g. through student supervision) or industry. Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, ICLR with specific focus on … ambiguity. Preferred qualifications : High-impact publications in top-tier conferences or other influence in the research community. 5+ years of hands-on experience leading teams building advanced ML/NLP/IR systems in academia (e.g. through student supervision) or for commercial applications. Extensive experience with deep learning and large-scale model training. Extensive experience working on agent-based systems More ❯

in either a professional data science position or a quantitative academic field Strong programming skills as evidenced by earlier work in data science or software engineering. Although your programming language of choice (e.g. R, MATLAB or C) is not important, we do require the ability to become a fluent Python programmer in a short timeframe An excellent command of … statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability to develop new algorithms when an innovative solution is needed as a fundamental skill More ❯

in either a professional data science position or a quantitative academic field Strong programming skills as evidenced by earlier work in data science or software engineering. Although your programming language of choice (e.g. R, MATLAB or C) is not important, we do require the ability to become a fluent Python programmer in a short timeframe An excellent command of … statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability to develop new algorithms when an innovative solution is needed as a fundamental skill More ❯

extraction. Benchmark and tune state-of-the-art LLMs for performance and cost efficiency. Incorporate trends like instruction tuning, RLHF, or LoRA fine-tuning. Embed domain-specific ontologies into NLP workflows. Evaluation and Optimization: Analyze models for quality, latency, sustainability, and cost; implement improvements. Own the ML-Ops for your Pod. Develop experiments for model evaluation and continuous improvement. Best … and LLM architectures: Experience with GPT-4, Claude, Gemini, Llama, Falcon, Mistral. Model performance and optimization: Fine-tuning and optimizing LLMs for quality, latency, sustainability, and cost. Programming and NLP tools: Advanced Python, frameworks like PyTorch, TensorFlow, Hugging Face, LangChain. MLOps and deployment: Docker, Kubernetes, Azure ML Studio, MLFlow. Cloud and AI infrastructure: Experience with Azure Cloud for scalable deployment. More ❯

track record of high performance and exceeding quotas Experience building and maintaining senior-level relationships with executives Experience selling complex enterprise level solutions, technical products, private deployments (AI/NLP solutions preferred) Experience working with channel partners to drive sales cycles and hit shared revenue goals High tolerance for ambiguity - as an early sales team member, you'll have to More ❯

in ambiguous problem spaces, and mentor junior team members. Strong collaboration and communication skills, with experience aligning technical approaches with cross-functional teams and stakeholders. Bonus Points Experience with NLP, image classifiers, deep learning, or large language models. Experience with experiment design and conducting A/B tests. Experience building shared or platform-style ML systems. Experience with Databricks More ❯

people award winner, an advocate of supporting women in engineering and developing their people to be the best they can be? We have an exciting opportunity for an experienced NLP Data Scientist who can architect and code algorithms that harness the power of internal data to join an ambitious Information Management Department within a highly regarded, scientific engineering/manufacturing … Easy Access to train station, Coffee Shops & Onsite Shop, Sports & Social Club and More Skills Required: Proficiency in Data Science techniques, including statistical models and ML algorithms. Expertise in NLP, with a keen understanding of LLM and RAG technologies. Strong development capabilities, particularly in Python. Experience with data exchange, processing, and storage frameworks (ETL, ESB, API, SQL, NoSQL, and More ❯