1 to 25 of 28 Natural Language Processing Jobs in Scotland

need for success To be successful in this role, you will be able to demonstrate: Practical and theoretical expertise in one or more AI/ML areas such as Natural Language Processing, Computer Vision, Reinforcement Learning, Agentic AI, Multimodal Models, Generative AI, Responsible AI, and Algorithmic Auditing. Knowledge of assessment techniques to evaluate AI systems for effectiveness More ❯

intelligent QA, multi-agent collaboration, and AI developer tools. Be part of internal engineering efforts, with responsibility of algorithms, modelling, engineering and product scaling and support. Requirements: PhD in NLP, deep learning, knowledge engineering, information retrieval, or related fields. At least 3 years of work experience in at least one of the following fields is REQUIRED: Knowledge engineering technologies (RDF … SPARQL, OWL, SKOS)/Natural Language Processing (LLM, agent, entity detection, question answering, etc.)/Machine Learning & Deep Learning (LSTM, transformer, etc.) . At least 2 (3-5 would be desirable) papers published on top conference/journal in the related fields like KDD, ISWC, ACL, NeurIPS, ICML, EMNLP, ICLR, AAAI, IJCAI, WWW, KR. Excellent software design More ❯

our cybersecurity capabilities. Key Responsibilities: · Design, develop, and deploy full-stack AI solutions with a focus on cybersecurity threat detection and response. · Apply AI/ML techniques such as NLP, supervised/unsupervised learning, and generative AI to real-world security data. · Integrate AI models into scalable applications using modern full-stack development tools and frameworks. · Collaborate with cybersecurity teams … experience in a cybersecurity operations or similar function. · Strong knowledge of cybersecurity principles, frameworks, and threat intelligence (e.g., MITRE ATT&CK). · Proficient in AI/ML technologies, including Natural Language Processing, Generative AI, and Machine Learning algorithms. · Experienced in full-stack development with proficiency in Python, C C#, or R. · Familiarity with AI libraries and tools More ❯

both supervised and unsupervised. Proficient programming skills with Python, including libraries such as NumPy, pandas, and scikit-learn, as well as R. Understanding and usage of the OpenAI API. NLP: tokenization, embeddings, sentiment analysis, basic transformers for text-heavy datasets. Experience with LLM & Prompt Engineering, including tools like LangChain, LangGraph, and Retrieval-Augmented Generation (RAG). Experience in anomaly detection More ❯

SSIS, Python, Java, Scala, XML/FpML and Power BI Solution architecture (Business, Functional, Technical) Data architecture, data lineage and all aspects of AI including, but not limited to, NLP, ML, deep learning and Generative AI Integration architecture Testing/quality engineering; experience of test automation will be beneficial Process Automation, BPM and Digital Platforms, e.g. Pega Cloud technology (knowledge More ❯

an organisation that encourages continuous personal development, and are keen to talk with good candidates Desirable but not essential Demonstrable interest in Artificial Intelligence, Machine Learning, Deep Learning, or Natural Language Processing.Some hands-on experience with AI concepts, libraries, or frameworks (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers, Keras, etc.) Familiarity with Python for AI/ML More ❯

an organisation that encourages continuous personal development, and are keen to talk with good candidate Desirable but not essential Demonstrable interest in Artificial Intelligence, Machine Learning, Deep Learning, or Natural Language Processing. Some hands-on experience with AI concepts, libraries, or frameworks (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers, Keras, etc.). Familiarity with Python for AI More ❯

Strong coding experience in Python and the ML/AI development ecosystem. Solid understanding and ideally hands-on experience with core Machine Learning concepts. Specialisation or strong exposure to NLP, LLMs, Gen AI OR Deep Learning frameworks (one area is fine) Prior experience delivering training, mentoring, or leading workshops or lectures. ( Trainer/Instructor/Lecturer/Teacher Consultant/ More ❯

Strong coding experience in Python and the ML/AI development ecosystem. Solid understanding and ideally hands-on experience with core Machine Learning concepts. Specialisation or strong exposure to NLP, LLMs, Gen AI OR Deep Learning frameworks (one area is fine) Prior experience delivering training, mentoring, or leading workshops or lectures. ( Trainer/Instructor/Lecturer/Teacher Consultant/ More ❯

Strong coding experience in Python and the ML/AI development ecosystem. Solid understanding and ideally hands-on experience with core Machine Learning concepts. Specialisation or strong exposure to NLP, LLMs, Gen AI OR Deep Learning frameworks (one area is fine) Prior experience delivering training, mentoring, or leading workshops or lectures. ( Trainer/Instructor/Lecturer/Teacher Consultant/ More ❯

Aveni is an award-winning technology company. We use advanced AI to enable scalable efficiency for financial services companies, combining world-leading Natural Language Processing (NLP) and Large Language Model (LLM) expertise with deep financial services domain experience to drive enterprise-wide productivity. Aveni harnesses the power of voice to drive unprecedented efficiency and oversight. We More ❯

the use of agentic GenAI. As Legal AI Engineer you will: Design and implement AI models tailored to legal text and documents (e.g., contracts, case law, regulations). Apply NLP techniques to extract structured insights from unstructured legal data. Collaborate with legal SMEs to translate domain knowledge into scalable machine learning solutions. Continuously evaluate model performance, ensuring accuracy, fairness, and … compliance. Help shape the data pipeline and MLOps practices for handling sensitive legal content securely. Required Experience: Solid experience with Python and ML/NLP libraries (e.g., spaCy, Hugging Face, TensorFlow/PyTorch). Experience building NLP or document analysis solutions, ideally for legal or compliance use cases. Strong understanding of legal language, structures, and workflows (e.g., contracts, clauses More ❯

Strong Efficacy experience Advanced knowledge of statistics, programming and/or clinical drug development process Advanced knowledge of computing applications such as Base SAS, SAS Graph and SAS Macro Language Advanced knowledge of relevant Data Standards (such as CDISC/ADaM/SDTM) Join IQVIA to see where your skills can take you Global exposure Variety of therapeutic areas … United Kingdom 20 hours ago Stirling, Scotland, United Kingdom 2 days ago Edinburgh, Scotland, United Kingdom 2 days ago Edinburgh, Scotland, United Kingdom 1 week ago Senior Data Scientist (Natural Language Processing) Edinburgh, Scotland, United Kingdom 2 months ago Edinburgh, Scotland, United Kingdom 2 weeks ago Edinburgh, Scotland, United Kingdom 1 day ago Senior AI Architect and More ❯

clients. You’ll be applying some of the SOTA research in AI to develop applications. As such we would expect you to have: Background in foundational Computer Vision/NLP Strong Software Engineering skills (3 years+) Developed LLM architecture and deployed LLM applications Uptodate with current trends in AI Some experience with applying latest techniques like RAG architecture, GenAI, Parallel More ❯

multiple organisations for collaborative tasks. Detail oriented with excellent prioritisation, and multitasking abilities. Ability to work collaboratively with minimal supervision. Familiarity with AI technologies, such as ChatGPT or similar natural language processing model Experience in the insurance and/or consulting or wider financial services sector. Why join our team: We help you be your best through More ❯

is highly visible to senior leadership and directly impacts multiple organization goals and beyond. BASIC QUALIFICATIONS 3+ years of scientists or machine learning engineers management experience Knowledge of ML, NLP, Information Retrieval and Analytics PREFERRED QUALIFICATIONS Experience building machine learning models or developing algorithms for business application Experience building complex software systems, especially involving deep learning, machine learning and computer More ❯

s committed to transforming returns management while contributing to a more sustainable future. Key job responsibilities -Design, develop, and evaluate highly innovative models for Natural Language Programming (NLP), Large Language Model (LLM), or Large Computer Vision projects. -Use SQL to query and analyze the data. -Use Python, Jupyter notebook, and Pytorch to train/test/deploy … modeling techniques to power our ML models BASIC QUALIFICATIONS - PhD, or Master's degree and 6+ years of applied research experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning - Experience with popular deep learning frameworks such as MxNet and Tensor Flow. PREFERRED QUALIFICATIONS - Experience in building machine learning models … for business application - Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects) - PhD in math/statistics/engineering or other equivalent quantitative discipline, or Master's degree - Experience in building Computer Vision (CV) systems. Our inclusive culture empowers Amazonians to deliver the best results for More ❯

both supervised and unsupervised. Proficient programming skills with Python, including libraries such as NumPy, pandas, and scikit-learn, as well as R. Understanding and usage of the OpenAI API. NLP: tokenization, embeddings, sentiment analysis, basic transformers for text-heavy datasets. Experience with LLM & Prompt Engineering, including tools like LangChain, LangGraph, and Retrieval-Augmented Generation (RAG). Experience in anomaly detection More ❯

team has grown to 75+ data scientists and engineers. Working collaboratively, the team is multi-disciplinary with the following skills and capabilities: machine learning, optimization, statistical modeling, signal detection, natural language processing, data visualization, generative AI, network/graph modeling, ETL, data pipelines, data architecture, ML engineering, communication, product management and strategy. We work with data from … deliverables Participate in team agile processes, and proactively contribute to team culture The minimum requirements for this position are: 4+ year experience shipping code to production environments Strong programming language skills in Python and SQL Experience building cloud native applications Great problem-solving and communication skills Knowledge and experience we are looking for includes: DevOps automation, idempotent deployment testing More ❯

similar penchant for deeply-technical problem solving and the ability to lead, mentor, and deliver while upholding Amazon’s leadership principles. BASIC QUALIFICATIONS - Master's degree - Knowledge of ML, NLP, Information Retrieval and Analytics - Experience directly managing scientists or machine learning engineers - Experience programming in Java, C++, Python or related language - Experience in building machine learning models for business More ❯

equivalent including being professionally qualified in relevant discipline, with a broad range of professional experience in management role(s). A2 Strong knowledge of more than one modern programming language used in research (typically Python, R, C++, Java, Julia, C). A3 Excellent understanding of best practice for producing reliable software and reproducible analyses, including version control, issue tracking … and optimising software to take advantage of GPU/HPC infrastructure. B2 Good knowledge and experience of more than one of the followings broad areas: Statistics; Health Data Science; Natural Language Processing; Large Language Models; Environmental Sustainability; Inequality; Trusted Research Environments; Digital Humanities. Skills Essential: C1 Excellent team leadership, planning, organisation, time and workload management skills More ❯

both supervised and unsupervised. Proficient programming skills with Python, including libraries such as NumPy, pandas, and scikit-learn, as well as R. Understanding and usage of the OpenAI API. NLP: tokenization, embeddings, sentiment analysis, basic transformers for text-heavy datasets. Experience with LLM & Prompt Engineering, including tools like LangChain, LangGraph, and Retrieval-Augmented Generation (RAG). Experience in anomaly detection More ❯

team has grown to 30+ data scientists and data engineers. Working collaboratively, the team is multi-disciplinary with the following skills and capabilities: machine learning, statistical modeling, signal detection, natural language processing, data visualization, network/graph modeling, ETL, data pipelines, data architecture, communication, product management and strategy. We work with data from a wide variety of More ❯

Knowledge Computing Researcher. In this role, you would be working as part of a high calibre team of engineers and researchers to build intelligent agent systems powered by large language models, knowledge graphs, and multi-modal semantic search. This is a unique opportunity to apply cutting-edge research to real-world AI systems with meaningful impact across applications such … research into production-ready applications across AI development tools, QA systems, and assistant use-cases Contribute to core algorithm development and support product scaling initiatives Key Requirements: PhD in NLP, Machine Learning, Knowledge Engineering, or related fields 3+ years of experience in at least one of: Knowledge technologies (RDF, SPARQL, OWL, SKOS); NLP (LLMs, entity detection, question answering, agent systems … Strong coding and software design skills Experience working across research and applied development in a collaborative environment Keywords: Knowledge Graphs/LLMs/Semantic Search/Knowledge Reasoning/NLP/Agent Systems/RAG/OWL/SPARQL/Transformers/Deep Learning/AI Assistants/QA Systems/Pytorch/TensorFlow/Graph Reasoning/Multi-Modal More ❯

the transition from existing TRE provider (Robertson Centre for Biostatistics) to long-term operational sustainability. 3. Support the delivery of key demonstrator AI/ML projects (digital pathology, imaging, NLP) that will shape the TRE's foundational workflows for integration into national health research infrastructure. 4. To play a key role to ensure all TRE activities adhere to ISO, NHS More ❯