1 to 25 of 82 Natural Language Processing Jobs in the East of England

Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience with model explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning … or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience with model explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning … or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience with model explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning … or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience with model explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning … or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience with model explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning … or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience with model explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning … or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience with model explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning … or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience with model explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning … or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience with model explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning … or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience with model explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning … or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience with model explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning … or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools (e.g., Spark, Hadoop, Beam). Understanding of NLP, computer vision, or time series analysis techniques. Knowledge of experiment tracking tools (e.g., MLflow, Weights & Biases). Experience with model explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning … or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

. Qualifications (Preferred for Senior Roles) Expertise in advanced ML areas such as Transformers, LLMs, NER, GANs, Reinforcement Learning, or Multimodal AI. Academic or industry experience in fields like Natural Language Processing, Computer Vision, or Deep Learning. For senior candidates, must have written publications in peer-reviewed journals or conferences (e.g., NeurIPS, ICML, ACL, CVPR). Demonstrated … Adecco operates as an Employment Agency and is an equal opportunities employer. We are on the client's supplier list for this role. Keywords AI Research, Machine Learning Engineer, NLP, Computer Vision, Deep Learning, PyTorch, TensorFlow, LLMs, Transformers, GANs, Reinforcement Learning, Data Science, Python, Cambridge AI Jobs, Applied AI, Research Scientist, Artificial Intelligence, ML Research, AI Innovation More ❯

combined with a passion for leveraging AI to solve meaningful problems. Key Responsibilities: Design, develop, and deploy scalable AI systems for production environments. Build and fine-tune models for natural language processing, computer vision, or predictive analytics. Collaborate with data scientists and engineers to optimise models for performance and reliability. Develop automated pipelines for data ingestion, model … models on cloud platforms (Azure) or containerised environments (Docker, Kubernetes). Proficiency in machine learning algorithms and advanced AI techniques, including transformer-based architectures. Hands-on experience with large language models (e.g., GPT, Langchain) or custom-built AI systems. Familiarity with DevOps tools and practices for deploying and managing AI systems. Strong problem-solving skills and the ability to More ❯

Python, SQL) Exploratory data analysis Data storytelling and visualization Ethics in data and AI Applied mathematics and statistics Data model measurement and testing Insight and decision making Machine learning Natural language processing Working with Generative AI – Large language models (LLMs) and image generation (ChatGPT, Gemini) Consulting Skills: Effective teamwork Business acumen Time management Stakeholder management Presentations More ❯

data protection and GDPR Understanding of Cybersecurity and common issues Extensive knowledge of using data science and AI techniques such as ML, simulation modelling, causal impact analysis, network analysis, NLP Desirable Knowledge of health technology Knowledge of NHS operations, policies, governance and organisational structures Skills Essential Confidence and skilled in adapting to new software and programming language Skilled in More ❯

to recruit a senior researcher to join our rapidly expanding Data and Decision Support Capability. You should have solid background in Machine Learning (ML) and/or statistical signal processing combined with excellent programming skills in Python and extensive experience in the use of libraries and toolboxes to support efficient development. The right candidate will join our Advanced Information … Processing (AIP) group, specialising in developing novel inference algorithms and the application of AI/ML to sequential (time-series) data and decision making. The candidate will have the opportunity to deliver a wide range of AI/ML research topics for customers across the space, defence, security and commercial sectors as well as into our internal BAE Systems … processing, data fusion, reinforcement learning, agent-based ML, autonomy, ML for signal processing, edge ML, image analysis and computer vision, generative AI, deep fake, LLMs, knowledge graphs, NLP, graph ML and others. You will have the opportunity to work with these colleagues in multi-disciplinary teams. Typical Responsibilities: Lead technical delivery of projects, leading junior researchers. Prepare and More ❯

bachelor’s degree or master’s degree in Computer Science, Data Science or related field. 5+ years of experience in machine learning or AI architecture roles, across ML/NLP/LLM systems 3+ years as an architect or technical lead with systems-level experience Proven track record of delivering AI solutions for complex scientific problems Experience with machine learning … algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn, spaCY), and data processing techniques. Demonstrated experience in developing and deploying machine learning models in production environments. Experience with AI Cloud Platforms (AWS SageMaker, Azure ML, or GCP Vertex AI) for scalable deployment of AI models. Strong time-management skills; able to complete projects in a timely manner, plan and More ❯

Senior AI Engineer IQVIA NLP Cambridge, UK We are looking for a Senior AI Engineer to lead the development of advanced machine learning solutions that address complex challenges in the pharmaceutical and healthcare sectors. In this role, you will drive the transformation of cutting-edge research into scalable, production-grade AI systems. You'll work across the full lifecycle-from … environment with real-world impact. Career growth through innovation, mentorship, and continuous learning. Competitive compensation and benefits This role is not eligible for UK visa sponsorship. The Team IQVIA NLP is a leading provider of Natural Language Processing solutions focussed on Human Data Science. NLP is a foundational technique for AI and ML and a critical enabler … for IQVIA's Connected Intelligence solutions and the delivery of clinical trials and studies. IQVIA NLP is an acknowledged leader in this space with a global customer base spanning Major Pharma companies, Healthcare Payers & Providers and Government. By using NLP, IQVIA and its customers leverage the value of unstructured patient data, social media and scientific literature, impacting pharmaceutical/MedTech More ❯

Amazon looking to push the boundaries of AI through science-led evaluations. If you're ambitious to make a difference to the future of AI, have a PhD in NLP, and like to turn ideas into reality, we'd love to hear from you. Role We are developing adversarial tests for Large Language Models (LLMs). We are looking … Chief Scientist to design, develop and deploy evaluation technologies that will create high value insights for AI engineers. These will involve providing assessments for several technologies that involve Large Language Models, including retrieval augmented systems (RAGs), recommender systems, and agentive systems. You will: Invent, experiment with, and launch new features, products and systems based on machine learning and MLLM. … conference papers. Collaborate with engineers, product partners locally and abroad, and join conversations with customers led by our marketing team. Essential skills PhD in Computer Science or related field (Natural Language Processing focus only) Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning Experience with LLM More ❯

Amazon looking to push the boundaries of AI through science-led evaluations. If you're ambitious to make a difference to the future of AI, have a PhD in NLP, and like to turn ideas into reality, we'd love to hear from you. Role We are developing adversarial tests for Large Language Models (LLMs). We are looking … Chief Scientist to design, develop and deploy evaluation technologies that will create high value insights for AI engineers. These will involve providing assessments for several technologies that involve Large Language Models, including retrieval augmented systems (RAGs), recommender systems, and agentive systems. You will: Invent, experiment with, and launch new features, products and systems based on machine learning and MLLM. … conference papers. Collaborate with engineers, product partners locally and abroad, and join conversations with customers led by our marketing team. Essential skills PhD in Computer Science or related field (Natural Language Processing focus only) Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning Experience with LLM More ❯

Amazon looking to push the boundaries of AI through science-led evaluations. If you're ambitious to make a difference to the future of AI, have a PhD in NLP, and like to turn ideas into reality, we'd love to hear from you. Role We are developing adversarial tests for Large Language Models (LLMs). We are looking … Chief Scientist to design, develop and deploy evaluation technologies that will create high value insights for AI engineers. These will involve providing assessments for several technologies that involve Large Language Models, including retrieval augmented systems (RAGs), recommender systems, and agentive systems. You will: Invent, experiment with, and launch new features, products and systems based on machine learning and MLLM. … conference papers. Collaborate with engineers, product partners locally and abroad, and join conversations with customers led by our marketing team. Essential skills PhD in Computer Science or related field (Natural Language Processing focus only) Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning Experience with LLM More ❯

Amazon looking to push the boundaries of AI through science-led evaluations. If you're ambitious to make a difference to the future of AI, have a PhD in NLP, and like to turn ideas into reality, we'd love to hear from you. Role We are developing adversarial tests for Large Language Models (LLMs). We are looking … Chief Scientist to design, develop and deploy evaluation technologies that will create high value insights for AI engineers. These will involve providing assessments for several technologies that involve Large Language Models, including retrieval augmented systems (RAGs), recommender systems, and agentive systems. You will: Invent, experiment with, and launch new features, products and systems based on machine learning and MLLM. … conference papers. Collaborate with engineers, product partners locally and abroad, and join conversations with customers led by our marketing team. Essential skills PhD in Computer Science or related field (Natural Language Processing focus only) Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning Experience with LLM More ❯

Amazon looking to push the boundaries of AI through science-led evaluations. If you're ambitious to make a difference to the future of AI, have a PhD in NLP, and like to turn ideas into reality, we'd love to hear from you. Role We are developing adversarial tests for Large Language Models (LLMs). We are looking … Chief Scientist to design, develop and deploy evaluation technologies that will create high value insights for AI engineers. These will involve providing assessments for several technologies that involve Large Language Models, including retrieval augmented systems (RAGs), recommender systems, and agentive systems. You will: Invent, experiment with, and launch new features, products and systems based on machine learning and MLLM. … conference papers. Collaborate with engineers, product partners locally and abroad, and join conversations with customers led by our marketing team. Essential skills PhD in Computer Science or related field (Natural Language Processing focus only) Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning Experience with LLM More ❯

Amazon looking to push the boundaries of AI through science-led evaluations. If you're ambitious to make a difference to the future of AI, have a PhD in NLP, and like to turn ideas into reality, we'd love to hear from you. Role We are developing adversarial tests for Large Language Models (LLMs). We are looking … Chief Scientist to design, develop and deploy evaluation technologies that will create high value insights for AI engineers. These will involve providing assessments for several technologies that involve Large Language Models, including retrieval augmented systems (RAGs), recommender systems, and agentive systems. You will: Invent, experiment with, and launch new features, products and systems based on machine learning and MLLM. … conference papers. Collaborate with engineers, product partners locally and abroad, and join conversations with customers led by our marketing team. Essential skills PhD in Computer Science or related field (Natural Language Processing focus only) Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning Experience with LLM More ❯