1,126 Nlp Engineer jobs in the United Kingdom

• Conduct research and development in Natural Language Processing (NLP) and related areas of Artificial Intelligence.
• Design, implement, and evaluate novel algorithms and models for tasks such as text classification, entity recognition, summarization, question answering, and machine translation.
• Work with large datasets, performing data preprocessing, feature engineering, and model training.
• Develop and fine-tune large language models (LLMs) for specific applications and domains.
• Implement and deploy AI models into production environments, ensuring scalability and efficiency.
• Collaborate with cross-functional teams, including product managers and software engineers, to integrate AI solutions into existing platforms and new products.
• Stay abreast of the latest advancements in AI, machine learning, and NLP research by reading academic papers and attending conferences.
• Publish research findings in top-tier academic conferences and journals.
• Contribute to the development of intellectual property through patents and technical documentation.
• Mentor junior researchers and engineers, fostering a culture of innovation and technical excellence.

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related quantitative field.
• Minimum of 5 years of experience in AI research and development, with a specialization in NLP.
• Proven track record of publishing research in leading AI/NLP conferences (e.g., NeurIPS, ICML, ACL, EMNLP).
• Deep understanding of machine learning and deep learning principles, with hands-on experience in frameworks like TensorFlow, PyTorch, or JAX.
• Expertise in NLP techniques, including transformer architectures, word embeddings, sequence-to-sequence models, and attention mechanisms.
• Proficiency in programming languages such as Python, and relevant libraries (e.g., Hugging Face Transformers, spaCy, NLTK).
• Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and MLOps practices is a plus.
• Strong analytical, problem-solving, and critical thinking skills.
• Excellent written and verbal communication skills, with the ability to clearly articulate complex technical concepts.
• Ability to work independently and thrive in a fast-paced, research-driven remote environment.

• Design, develop, and implement state-of-the-art NLP models and algorithms for various applications, including text classification, sentiment analysis, topic modeling, machine translation, and question answering.
• Work with large datasets, perform data preprocessing, feature engineering, and model training.
• Evaluate and optimise model performance, ensuring accuracy, scalability, and efficiency.
• Collaborate with software engineers to integrate ML models into production systems.
• Stay current with the latest research and advancements in NLP and ML, and apply them to solve real-world problems.
• Contribute to the architectural design of ML systems and pipelines.
• Conduct experiments, analyse results, and present findings to technical and non-technical stakeholders.
• Mentor junior engineers and contribute to the growth of the ML team.
• Identify opportunities for leveraging AI and ML to enhance existing products or create new ones.
• Ensure ethical considerations and bias mitigation are addressed in model development.
• Collaborate with domain experts to gather requirements and define problem statements.

• Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related quantitative field.
• 5+ years of hands-on experience in Machine Learning engineering, with a strong focus on NLP.
• Proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, spaCy, NLTK, Hugging Face Transformers.
• Strong understanding of deep learning architectures for NLP (e.g., LSTMs, Transformers, BERT, GPT).
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices.
• Excellent problem-solving skills and the ability to tackle complex technical challenges.
• Strong communication and collaboration skills.
• Experience with big data technologies (e.g., Spark) is a plus.
• Proven track record of deploying ML models into production environments.

• Design, develop, train, and deploy advanced Machine Learning models for NLP tasks, including but not limited to text classification, named entity recognition, machine translation, question answering, and text summarization.
• Implement and fine-tune state-of-the-art NLP architectures such as Transformers (e.g., BERT, GPT variants), LSTMs, and CNNs.
• Process and analyze large-scale text datasets, ensuring data quality and preparing it for model training.
• Collaborate with product managers, data scientists, and other engineers to understand business requirements and translate them into technical solutions.
• Develop and maintain robust ML pipelines for experimentation, training, and inference.
• Evaluate model performance using appropriate metrics and conduct rigorous testing to ensure accuracy and reliability.
• Optimize ML models for performance, scalability, and efficiency in production environments.
• Stay abreast of the latest research and advancements in NLP and ML, and apply them to our projects.
• Contribute to the team's knowledge sharing through code reviews, documentation, and presentations.
• Ensure ethical considerations and bias mitigation are integrated into the ML development lifecycle.
• Deploy models using cloud platforms and MLOps best practices.
• Debug and resolve issues related to model performance and data pipelines.

• Master's or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related quantitative field.
• Minimum of 5 years of professional experience in Machine Learning, with a strong focus on Natural Language Processing.
• Proven expertise in Python and common ML libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, Keras.
• Deep understanding of NLP concepts, algorithms, and techniques.
• Experience with large language models (LLMs) and their practical applications.
• Proficiency in data manipulation and analysis libraries like Pandas and NumPy.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and MLOps tools.
• Strong software engineering skills, including experience with version control (e.g., Git) and CI/CD.
• Excellent analytical, problem-solving, and critical thinking abilities.
• Strong communication and collaboration skills, with the ability to work effectively in a remote team.
• Experience with distributed training and large-scale data processing is a plus.

• Develop, train, and deploy advanced NLP models and algorithms using state-of-the-art techniques.
• Process and analyze large volumes of text data to extract meaningful insights.
• Build and maintain robust machine learning pipelines for NLP tasks.
• Collaborate with data scientists and software engineers to integrate NLP solutions into existing and new products.
• Fine-tune pre-trained language models (e.g., BERT, GPT) for specific applications.
• Evaluate model performance, identify areas for improvement, and implement optimizations.
• Stay current with the latest research and developments in NLP and machine learning.
• Contribute to the architectural design and scalability of our NLP infrastructure.
• Mentor junior engineers and share expertise within the team.
• Participate in code reviews and ensure adherence to best practices in software development.
• Communicate technical findings and project updates to stakeholders effectively.
• Explore and implement new NLP techniques for tasks like question answering, summarization, and text generation.

• Master's or PhD in Computer Science, Artificial Intelligence, Linguistics, or a related field with a focus on NLP.
• A minimum of 5 years of professional experience in machine learning engineering, with a specialization in NLP.
• Proficiency in Python and ML libraries such as TensorFlow, PyTorch, Hugging Face Transformers, and NLTK/spaCy.
• Solid understanding of NLP concepts, including embeddings, attention mechanisms, and various model architectures.
• Experience with cloud platforms (AWS, Azure, GCP) and ML deployment strategies.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities, comfortable working in a hybrid environment.
• Experience with containerization technologies (e.g., Docker, Kubernetes) is a plus.
• Familiarity with data annotation and management for NLP tasks.
• Must be eligible to work in the UK and able to attend the Edinburgh office periodically.

• Lead the design, development, and implementation of production-ready NLP models and systems.
• Architect scalable and robust machine learning pipelines for data processing, model training, and deployment.
• Collaborate with product managers and data scientists to define NLP requirements and translate them into technical solutions.
• Mentor and guide a team of machine learning engineers and researchers, fostering a collaborative and innovative environment.
• Stay at the forefront of NLP research and advancements, identifying and evaluating new technologies and methodologies.
• Optimize model performance, efficiency, and scalability for large-scale applications.
• Develop and maintain best practices for code quality, testing, and deployment in ML systems.
• Contribute to the strategic vision for AI and NLP within the organization.
• Drive the end-to-end lifecycle of machine learning projects, from conceptualization to production deployment and monitoring.
• Effectively communicate complex technical concepts to both technical and non-technical stakeholders in a remote setting.
• Champion the ethical development and deployment of NLP technologies.

• Master's or PhD in Computer Science, Computational Linguistics, Artificial Intelligence, or a related field.
• Extensive experience (7+ years) in machine learning, with a strong specialization in NLP.
• Proven experience leading ML projects and/or teams.
• Deep understanding of core NLP tasks (e.g., tokenization, POS tagging, named entity recognition, parsing) and modern techniques (e.g., Transformers, BERT, GPT).
• Proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Experience with ML deployment strategies and MLOps practices.
• Strong software engineering skills, including experience with version control (Git) and CI/CD.
• Excellent problem-solving skills and the ability to tackle ambiguous challenges.
• Outstanding communication and leadership abilities, particularly in a remote team setting.
• Experience with cloud platforms (AWS, Azure, GCP) is a significant advantage.
• A passion for building impactful NLP solutions and driving innovation.

• Design, develop, and implement advanced NLP models, including but not limited to sentiment analysis, text classification, named entity recognition, machine translation, and question answering systems.
• Build and optimize robust data pipelines for training and evaluating machine learning models.
• Collaborate with product managers, researchers, and other engineers to define project requirements and translate them into scalable ML solutions.
• Stay current with the latest research and advancements in NLP and machine learning, and explore opportunities to integrate novel techniques.
• Deploy and maintain machine learning models in production environments, ensuring high availability and performance.
• Conduct thorough experimentation, model evaluation, and performance tuning to achieve optimal results.
• Develop and implement strategies for data augmentation, transfer learning, and few-shot learning to address data sparsity challenges.
• Mentor junior engineers and contribute to the team's technical growth and best practices.
• Write clean, well-documented, and efficient code in Python or other relevant programming languages.
• Contribute to the architectural design of our ML infrastructure and systems.
• Troubleshoot and resolve issues related to model performance and deployment.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• 5+ years of professional experience in machine learning, with a significant focus on NLP.
• Proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers.
• Deep understanding of NLP techniques, algorithms, and frameworks (e.g., LSTMs, Transformers, BERT, GPT).
• Experience with data preprocessing, feature engineering, and model evaluation for text data.
• Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.
• Strong analytical, problem-solving, and critical thinking skills.
• Excellent communication and collaboration abilities.
• Experience with distributed computing frameworks (e.g., Spark) is a plus.

AI Engineer - Data Science

Hybrid | London, England | Engineering

Overview

The Explore Group are partnered with one of our Tier 1 clients to secure AI Engineers with strong data science expertise who are eager to develop and deliver innovative AI solutions for large scale organisations. This role requires a combination of technical skills and business understanding, working with advanced AI technologies to create impactful data driven applications.

Responsibilities

• Partner with enterprise clients to understand requirements and design tailored AI and data science solutions
• Apply statistical modelling, machine learning, and programming expertise to solve complex problems
• Explore and implement modern AI technologies including large language models, retrieval augmented generation, and advanced automation tools
• Deliver production ready solutions that integrate into existing client environments
• Engage with stakeholders at different levels, translating technical approaches into clear business outcomes
• Stay up to date with rapidly evolving AI tools and actively incorporate them into solution design

Requirements

• Strong background in data science and machine learning with solid understanding of statistics and programming
• Exposure to MLOps and experience deploying models into production environments
• Interest and practical experience in using emerging AI technologies such as co pilots, agentic frameworks, and generative AI applications
• Proven ability to manage client expectations and deliver high quality solutions in a collaborative environment
• Excellent communication skills with the ability to present technical concepts to both technical and non technical audiences

Benefits

We offer a supportive and flexible work environment with a comprehensive benefits package including:

• 25 days of annual leave plus bank holidays
• Share options and pension scheme
• Health and dental insurance options
• Professional learning and development budget
• Cycle to work scheme and technology allowance
• Referral bonus scheme
• Opportunities to work abroad for limited periods
• Regular team socials and office perks

AI Engineer - Data Science

Hybrid | London, England | Engineering

Overview

The Explore Group are partnered with one of our Tier 1 clients to secure AI Engineers with strong data science expertise who are eager to develop and deliver innovative AI solutions for large scale organisations. This role requires a combination of technical skills and business understanding, working with advanced AI technologies to create impactful data driven applications.

Responsibilities

• Partner with enterprise clients to understand requirements and design tailored AI and data science solutions
• Apply statistical modelling, machine learning, and programming expertise to solve complex problems
• Explore and implement modern AI technologies including large language models, retrieval augmented generation, and advanced automation tools
• Deliver production ready solutions that integrate into existing client environments
• Engage with stakeholders at different levels, translating technical approaches into clear business outcomes
• Stay up to date with rapidly evolving AI tools and actively incorporate them into solution design

Requirements

• Strong background in data science and machine learning with solid understanding of statistics and programming
• Exposure to MLOps and experience deploying models into production environments
• Interest and practical experience in using emerging AI technologies such as co pilots, agentic frameworks, and generative AI applications
• Proven ability to manage client expectations and deliver high quality solutions in a collaborative environment
• Excellent communication skills with the ability to present technical concepts to both technical and non technical audiences

Benefits

We offer a supportive and flexible work environment with a comprehensive benefits package including:

• 25 days of annual leave plus bank holidays
• Share options and pension scheme
• Health and dental insurance options
• Professional learning and development budget
• Cycle to work scheme and technology allowance
• Referral bonus scheme
• Opportunities to work abroad for limited periods
• Regular team socials and office perks