1 to 25 of 66 Permanent Natural Language Processing Jobs in the South East

We're Hiring: Lead Expert - NLP & Machine Learning for Investment Metrics 📍 Location: Nice (France) or London (UK) 🏢 Company: Scientific Beta 🔬 About Us A subsidiary of SGX Group, Scientific Beta is a leading provider of enhanced systematic equity strategies grounded in rigorous research. Its evidence-based indices integrating sustainability and financial goals enable global investors to make well-informed portfolio decisions … a key role in developing new index methodologies. 🧠 About the Role Scientific Beta is seeking a highly experienced and innovative Lead Expert in Natural Language Processing (NLP) and Machine Learning (ML) to spearhead the development of next-generation sustainability and financial metrics. This is a unique opportunity to leverage cutting-edge language models and insights at … instrumental in driving the research, development, validation and product implementation of novel metrics by extracting valuable information from textual data. 📌 Key Responsibilities Lead the conceptualization, design, and implementation of NLP and ML models for extracting insights related to sustainability and financial performance from diverse textual sources. Develop and apply state-of-the-art language models to extract relevant information More ❯

We're Hiring: Lead Expert - NLP & Machine Learning for Investment Metrics 📍 Location: Nice (France) or London (UK) 🏢 Company: Scientific Beta 🔬 About Us A subsidiary of SGX Group, Scientific Beta is a leading provider of enhanced systematic equity strategies grounded in rigorous research. Its evidence-based indices integrating sustainability and financial goals enable global investors to make well-informed portfolio decisions … a key role in developing new index methodologies. 🧠 About the Role Scientific Beta is seeking a highly experienced and innovative Lead Expert in Natural Language Processing (NLP) and Machine Learning (ML) to spearhead the development of next-generation sustainability and financial metrics. This is a unique opportunity to leverage cutting-edge language models and insights at … instrumental in driving the research, development, validation and product implementation of novel metrics by extracting valuable information from textual data. 📌 Key Responsibilities Lead the conceptualization, design, and implementation of NLP and ML models for extracting insights related to sustainability and financial performance from diverse textual sources. Develop and apply state-of-the-art language models to extract relevant information More ❯

We're Hiring: Lead Expert - NLP & Machine Learning for Investment Metrics 📍 Location: Nice (France) or London (UK) 🏢 Company: Scientific Beta 🔬 About Us A subsidiary of SGX Group, Scientific Beta is a leading provider of enhanced systematic equity strategies grounded in rigorous research. Its evidence-based indices integrating sustainability and financial goals enable global investors to make well-informed portfolio decisions … a key role in developing new index methodologies. 🧠 About the Role Scientific Beta is seeking a highly experienced and innovative Lead Expert in Natural Language Processing (NLP) and Machine Learning (ML) to spearhead the development of next-generation sustainability and financial metrics. This is a unique opportunity to leverage cutting-edge language models and insights at … instrumental in driving the research, development, validation and product implementation of novel metrics by extracting valuable information from textual data. 📌 Key Responsibilities Lead the conceptualization, design, and implementation of NLP and ML models for extracting insights related to sustainability and financial performance from diverse textual sources. Develop and apply state-of-the-art language models to extract relevant information More ❯

About you: You will be a skilled Conversational AI – Technical Trainer to create and deliver in-depth training programs on conversational AI and natural language processing (NLP). The ideal candidate will have a hands-on technical training session covering conversational AI, suitable for those with some background and practical experience in the field, including building and … Requirements: Modify training to suit specific industries, ensuring it aligns with best practices and regulatory standards. Create Training Programs and Materials: Develop modules and engaging resources on conversational AI, NLP, and chatbot design. Assess Training Impact and Learner Progress: Evaluate participant understanding and refine content based on feedback and performance. Stay Current with Industry Trends and Tools: Update training materials … with the latest developments in AI, NLP, and machine learning. Qualifications: Bachelor’s or Master’s in Computer Science, Linguistics, AI, or related fields. Experience working in AI/NLP with experience in conversational AI development. Proven experience delivering technical training on conversational AI to diverse audiences. Holding certification that relevant AI/ML certifications (e.g., Google Professional ML Engineer More ❯

improve customer satisfaction and conversion. Key Responsibilities Design and maintain analytical models, dashboards, and visualisations using tools such as Python, R, Tableau, or Power BI. Apply machine learning and natural language processing techniques to both structured and unstructured data sources. Monitor key CX metrics (NPS, CSAT, conversion rates) to identify emerging trends, opportunities, and risks. Conduct exploratory … tools such as Python, R, Tableau, or Power BI. Interest or experience in customer experience and Voice of Customer (VoC) insights. Bonus skills (not required): Experience with predictive modelling, NLP, or large language models. Exposure to customer journey mapping. Knowledge of additional languages (French, Spanish, or German). What's on Offer Opportunities to work across multiple European locations. More ❯

you will be expected to: Build Agentic AI and GenAI solutions, from PoC to production, using agile methodologies and best practices. Apply advanced analytical techniques, such as machine learning, natural language processing, computer vision, and deep learning, to extract insights and generate solutions from structured and unstructured data. Build data pipelines, models, and AI applications, using cloud More ❯

you will be expected to: Build Agentic AI and GenAI solutions, from PoC to production, using agile methodologies and best practices. Apply advanced analytical techniques, such as machine learning, natural language processing, computer vision, and deep learning, to extract insights and generate solutions from structured and unstructured data. Build data pipelines, models, and AI applications, using cloud More ❯

you will be expected to: Build Agentic AI and GenAI solutions, from PoC to production, using agile methodologies and best practices. Apply advanced analytical techniques, such as machine learning, natural language processing, computer vision, and deep learning, to extract insights and generate solutions from structured and unstructured data. Build data pipelines, models, and AI applications, using cloud More ❯

authentication/authorization standards, and API lifecycle best practices; familiarity with Microsoft Graph API is a plus. Experience & Knowledge Requirements Good knowledge of generative AI, machine learning, deep learning, natural language processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries More ❯

authentication/authorization standards, and API lifecycle best practices; familiarity with Microsoft Graph API is a plus. Experience & Knowledge Requirements Good knowledge of generative AI, machine learning, deep learning, natural language processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries More ❯

authentication/authorization standards, and API lifecycle best practices; familiarity with Microsoft Graph API is a plus. Experience & Knowledge Requirements Good knowledge of generative AI, machine learning, deep learning, natural language processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries More ❯

years of professional experience in Python programming language. Solid understanding of machine learning algorithms, tools, and techniques, such as supervised. and unsupervised learning, transformer models, deep learning, computer vision, natural language processing, etc. Experience with common ML libraries and frameworks such as TensorFlow, PyTorch, Keras, Scikit-learn. Ability to work independently and collaboratively with multi-functional teams … ML tools such as Mlflow for model lifecycle management. Experience in building ML models in production using AWS ecosystem, especially ML related services such as SageMaker. Familiarity with large language models (LLM). Proficiency in multiple programming languages. Understanding of containerization technologies like Docker and orchestration tools like Airflow. We've got your back... We offer a range of More ❯

team on a contract basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers More ❯

team on a contract basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers More ❯

team on a contract basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers More ❯

Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. Experience with CI/CD, automated testing, and More ❯

regulatory intelligence. We give organisations the business information and analytics they need to make better, more impactful decisions. We are building powerful new decision tools that use machine learning, natural language processing, visualisation and artificial intelligence that aid and enhance decision making. More ❯

regulatory intelligence. We give organisations the business information and analytics they need to make better, more impactful decisions. We are building powerful new decision tools that use machine learning, natural language processing, visualisation and artificial intelligence that aid and enhance decision making. More ❯

regulatory intelligence. We give organisations the business information and analytics they need to make better, more impactful decisions. We are building powerful new decision tools that use machine learning, natural language processing, visualisation and artificial intelligence that aid and enhance decision making. More ❯

Python and SQL; familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Machine learning expertise: Hands-on experience in supervised and unsupervised learning, with exposure to NLP, computer vision, or deep learning a plus. Data visualisation: Proficiency in Tableau, Power BI, or similar. Problem-solving mindset: Ability to translate complex technical problems into business solutions. 🌟 It’s More ❯

Python and SQL; familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Machine learning expertise: Hands-on experience in supervised and unsupervised learning, with exposure to NLP, computer vision, or deep learning a plus. Data visualisation: Proficiency in Tableau, Power BI, or similar. Problem-solving mindset: Ability to translate complex technical problems into business solutions. 🌟 It’s More ❯

Be Delivering Collaborate with clients to identify business challenges and AI opportunities. Design and develop AI models and algorithms to meet client needs. Provide technical expertise in machine learning, NLP, and computer vision. Conduct data analysis and preprocessing for model training. Deploy AI models into production environments and monitor performance. Offer training and support on AI tools and best practices. More ❯

Be Delivering Collaborate with clients to identify business challenges and AI opportunities. Design and develop AI models and algorithms to meet client needs. Provide technical expertise in machine learning, NLP, and computer vision. Conduct data analysis and preprocessing for model training. Deploy AI models into production environments and monitor performance. Offer training and support on AI tools and best practices. More ❯

technical expertise with strategic client engagement. As a Senior/Principal AI Architect, you will: Lead the design and delivery of AI and cloud-native architectures, including Generative AI, NLP, and LLM solutions. Act as a trusted advisor to senior stakeholders, guiding AI roadmaps and strategy. Translate complex business needs into scalable AI-driven solutions across public cloud, edge, and More ❯

technical expertise with strategic client engagement. As a Senior/Principal AI Architect, you will: Lead the design and delivery of AI and cloud-native architectures, including Generative AI, NLP, and LLM solutions. Act as a trusted advisor to senior stakeholders, guiding AI roadmaps and strategy. Translate complex business needs into scalable AI-driven solutions across public cloud, edge, and More ❯