1 to 25 of 1,273 Permanent Natural Language Processing Jobs

pipelines (e.g., DevOps pipelines, Git actions). Knowledge of infrastructure as code (e.g., Terraform, ARM Template, Databricks Asset Bundles). Understanding of advanced machine learning techniques, including graph-based processing, computer vision, natural language processing, and simulation modeling. Experience with generative AI and LLMs, such as LLamaIndex and LangChain Understanding of MLOps or LLMOps. Familiarity with More ❯

Senior Data Scientist (Natural Language Processing) Total Remuneration: £57,879 to £68,146 Pay Supplement: The base salary for this role is £46,677 - £54,957 This job qualifies for Digital, Data and Technology Annual Pay supplement of 24% which is included in the total remuneration above. Pension: 28.97% of base salary (RoS contribution) Annual Leave … Digital Humanities (e.g. Computational Linguistics, Data Science, Computer Science or a related field), or equivalent experience. Broad knowledge of data science tools and approaches, with in-depth knowledge of language processing techniques. Strong analytical skills and experience with ability to critically select, combine and apply a range of scientific methods. Expert understanding and application of Natural Language Processing techniques. Experience of text mining, data annotation and model development. Awareness of Data and AI Governance considerations - ethics, transparency and explainability, licensing and regulation. Commercial awareness and awareness of product delivery life cycle (within an Agile delivery context). Competencies At application stage, you will be scored against the bolded Competencies and against the remaining all Competencies More ❯

Senior Data Scientist (Natural Language Processing) Total Remuneration: £57,879 to £68,146 Pay Supplement: The base salary for this role is £46,677 - £54,957 This job qualifies for Digital, Data and Technology Annual Pay supplement of 24% which is included in the total remuneration above. Pension: 28.97% of base salary (RoS contribution) Annual Leave … Digital Humanities (e.g. Computational Linguistics, Data Science, Computer Science or a related field), or equivalent experience. Broad knowledge of data science tools and approaches, with in-depth knowledge of language processing techniques. Strong analytical skills and experience with ability to critically select, combine and apply a range of scientific methods. Expert understanding and application of Natural Language Processing techniques. Experience of text mining, data annotation and model development. Awareness of Data and AI Governance considerations – ethics, transparency and explainability, licensing and regulation. Commercial awareness and awareness of product delivery life cycle (within an Agile delivery context). Competencies At application stage, you will be scored against the bolded Competencies and against the remaining all Competencies More ❯

learning architectures. Practical experience with, or demonstrable capability for, applications of Generative AI, Large Language Models (LLMs), and related areas such as Natural Language Processing (NLP) or Computer Vision, relevant to business solutions. Solid understanding of foundational statistics and experimental design. Familiarity with or experience on cloud platforms Impact and Achievements: As a Principal Data Scientist More ❯

learning architectures. · Practical experience with, or demonstrable capability for, applications of Generative AI, Large Language Models (LLMs), and related areas such as Natural Language Processing (NLP) or Computer Vision, relevant to business solutions. · Solid understanding of foundational statistics and experimental design. · Familiarity with or experience on cloud platforms Impact and Achievements: As a Principal Data Scientist More ❯

is crucial to our mission of making the world safer by empowering the human mind with the right information at the right time. Scope of Work: Design and improve NLP models for text analysis, entity recognition, and relationship extraction from web content. Analyze data to identify patterns and insights that can enhance our platform's capabilities. Research and evaluate algorithms … insights to users and stakeholders. Apply responsible AI practices in all aspects of model development. Analyze model performance, diagnose issues, and recommend improvements. Research and evaluate emerging technologies in NLP, information retrieval, and ML. Document methodologies, model architectures, and experimental results. Mentor junior team members and contribute to the data science community of practice. Your Profile: Bachelor's or Master … data science libraries (NumPy, Pandas, scikit-learn). Experience with SQL for data querying and analysis. Solid understanding of machine learning algorithms, statistical methods, and predictive modeling. Experience with NLP techniques for text analysis, classification, and information extraction. Knowledge of deep learning frameworks such as PyTorch or TensorFlow. Experience with data visualization tools (Matplotlib, Seaborn, Plotly, or similar). Strong More ❯

Perform data cleansing and preprocessing to ensure data quality and integrity. • Create data visualizations and interactive dashboards to present findings and insights. • Apply natural language processing (NLP) techniques for unstructured data analysis and text mining. • Develop algorithms for pattern recognition, clustering, and classification of data. • Communicate findings and recommendations to stakeholders through reports, presentations, and data storytelling. … experience supporting a component of the DoD. • Development experience in mid-level languages, like Java, C++, Python, or SQL • Proficiency in Python. • Experience with Spark, DataBricks, and Structured Query Language (SQL) • Experience in Data wrangling, Machine Learning, Data Visualization, Database Management, Cloud Computing, and Data Governance. • Experience documenting decision charts, processes, and standard operating procedures • Experience building briefings and More ❯

and Scale Data Science Use Cases Develop and deploy complex analytical models and insights to inform strategic decisions Implement data science solutions, including but not limited to predictive models, NLP, and GenAI applications Scale proof-of-concept data science ideas and products into maintainable production software services; Leverage best practices for production-ready code development and DevOps to build solutions More ❯

complex datasets related to computer and information science Develop and implement predictive models, classification algorithms, and clustering techniques to support research goals Apply natural language processing (NLP), computer vision, or other domain-specific algorithms as required by the research Design, develop, and optimize advanced algorithms that can process large-scale data efficiently, with a focus on performance … advancements in data science, AI, and information systems, and apply relevant findings to ongoing projects Work closely with data engineers to build and optimize data pipelines that facilitate the processing and analysis of large datasets Utilize cloud platforms and big data technologies (e.g., AWS, Azure, Hadoop, Spark) for efficient data processing and model deployment Design and implement robust … tools (e.g., Matplotlib, Seaborn, Tableau, Power BI) to present insights effectively Strong understanding of big data technologies (e.g., Hadoop, Spark) and cloud platforms (AWS, Azure, Google Cloud) Familiarity with NLP, computer vision, or other specialized techniques relevant to computer and information research Experience with version control systems (e.g., Git) and software development practices Strong background in applying data science to More ❯

matter expert on a wide range of ML techniques and optimizations. Provide in-depth knowledge of ML algorithms, frameworks, and techniques. Enhance ML workflows through advanced proficiency in large language models (LLMs) and related techniques. Conduct experiments using the latest ML technologies, analyze results, and tune models. Collaborate with engineering teams to bring experimental results into production solutions, owning … Python (intermediate proficiency required), Java, C/C++, etc. Experience applying data science and ML techniques to solve business problems. Solid background in Natural Language Processing (NLP) and Large Language Models (LLMs). Hands-on experience with machine learning and deep learning methods. Deep understanding of deep learning frameworks such as PyTorch or TensorFlow. Experience in More ❯

matter expert on a wide range of ML techniques and optimizations. Provides in-depth knowledge of ML algorithms, frameworks, and techniques. Enhances ML workflows through advanced proficiency in large language models (LLMs) and related techniques. Conducts experiments using latest ML technologies, analyzing results, tuning models Provides has Hands on coding to bring the experimental results into production solutions by … C/C++, etc. Intermediate Python is a must. Experience in applying data science, ML techniques to solve business problems. Solid background in Natural Language Processing (NLP) and Large Language Models (LLMs) Hands-on experience with machine learning and deep learning methods. Deep understanding and expertise in deep learning frameworks such as PyTorch or TensorFlow. Experience … with Ray, MLFlow, and/or other distributed training frameworks. In-depth understanding of Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies. Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods. Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker More ❯

matter expert on a wide range of ML techniques and optimizations. Provides in-depth knowledge of ML algorithms, frameworks, and techniques. Enhances ML workflows through advanced proficiency in large language models (LLMs) and related techniques. Conducts experiments using latest ML technologies, analyzing results, tuning models Provides has Hands on coding to bring the experimental results into production solutions by … C/C++, etc. Intermediate Python is a must. Experience in applying data science, ML techniques to solve business problems. Solid background in Natural Language Processing (NLP) and Large Language Models (LLMs) Hands-on experience with machine learning and deep learning methods. Deep understanding and expertise in deep learning frameworks such as PyTorch or TensorFlow. Experience … with Ray, MLFlow, and/or other distributed training frameworks. In-depth understanding of Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies. Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods. Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker More ❯

matter expert on a wide range of ML techniques and optimizations. Provides in-depth knowledge of ML algorithms, frameworks, and techniques. Enhances ML workflows through advanced proficiency in large language models (LLMs) and related techniques. Conducts experiments using latest ML technologies, analyzing results, tuning models Provides has Hands on coding to bring the experimental results into production solutions by … C/C++, etc. Intermediate Python is a must. Experience in applying data science, ML techniques to solve business problems. Solid background in Natural Language Processing (NLP) and Large Language Models (LLMs) Hands-on experience with machine learning and deep learning methods. Deep understanding and expertise in deep learning frameworks such as PyTorch or TensorFlow. Experience … with Ray, MLFlow, and/or other distributed training frameworks. In-depth understanding of Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies. Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods. Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker More ❯

a Data Scientist, this role plays a crucial role in delivering the generative artificial intelligence (GenAI) solutions for our clients. This position requires a deep understanding of machine learning, natural language processing, and generative models, combined with problem-solving skills and a passion for innovation. Key job responsibilities 1. Generative AI Model Development: -Design and develop generative … AI models, including language models, image generation models, and multimodal models. -Explore and implement advanced techniques in areas such as transformer architectures, attention mechanisms, and self-supervised learning. -Conduct research and stay up-to-date with the latest advancements in the field of generative AI. 2. Data Acquisition and Preprocessing: -Identify and acquire relevant data sources for training generative … learning models, with a strong focus on generative AI techniques. - Proficiency in programming languages such as Python, PyTorch, or TensorFlow, and experience with deep learning frameworks. - Strong background in natural language processing, computer vision, or multimodal learning. - Ability to communicate technical concepts to both technical and non-technical audiences. PREFERRED QUALIFICATIONS - Experience with large language models More ❯

tune models for regression, classification, clustering, and deep learning. Explore and implement state-of-the-art AI approaches such as transformer models, generative AI, and reinforcement learning. Expertise in natural language processing to analyze and generate insights from unstructured text data. Advanced Analytics and Insights Extract actionable insights from structured and unstructured datasets to support strategic decision More ❯

product strategy. In this role, you will: Lead AI strategy and execution in a high-ambiguity environment. Build, train, and deploy state-of-the-art models (e.g., deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures). Design infrastructure for data ingestion, annotation, experimentation, model versioning, and monitoring. Collaborate closely with product, design, and DevOps to integrate … product strategy. In this role, you will: Lead AI strategy and execution in a high-ambiguity environment. Build, train, and deploy state-of-the-art models (e.g., deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures). Design infrastructure for data ingestion, annotation, experimentation, model versioning, and monitoring. Collaborate closely with product, design, and DevOps to integrate … stealth-mode or early-stage startup, ideally taking an AI product from 0 → 1. Background in a relevant domain (e.g., healthcare AI, autonomous systems, finance, robotics, computer vision, or NLP). Hands-on experience with large-scale language models (LLMs) and prompt engineering (e.g., GPT, BERT, T5 family). Familiarity with on-device or edge-AI deployments (e.g., TensorFlow More ❯

product strategy. In this role, you will: Lead AI strategy and execution in a high-ambiguity environment. Build, train, and deploy state-of-the-art models (eg, deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures). Design infrastructure for data ingestion, annotation, experimentation, model versioning, and monitoring. Collaborate closely with product, design, and DevOps to integrate … stealth-mode or early-stage startup, ideally taking an AI product from 0 - 1. Background in a relevant domain (eg, healthcare AI, autonomous systems, finance, robotics, computer vision, or NLP). Hands-on experience with large-scale language models (LLMs) and prompt engineering (eg, GPT, BERT, T5 family). Familiarity with on-device or edge-AI deployments (eg, TensorFlow More ❯

product strategy. In this role, you will: • Lead AI strategy and execution in a high-ambiguity environment. • Build, train, and deploy state-of-the-art models (e.g., deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures). • Design infrastructure for data ingestion, annotation, experimentation, model versioning, and monitoring. • Collaborate closely with product, design, and DevOps to integrate … stealth-mode or early-stage startup, ideally taking an AI product from 0 → 1 • Background in a relevant domain (e.g., healthcare AI, autonomous systems, finance, robotics, computer vision, or NLP). • Hands-on experience with large-scale language models (LLMs) and prompt engineering (e.g., GPT, BERT, T5 family). • Familiarity with on-device or edge-AI deployments (e.g., TensorFlow More ❯

The position will report directly to the New York City-based Solutions Center Manager. Tasks may be supervised by other members of the Solutions Center team. Key Responsibilities Data Processing: Analyze large, complex datasets to identify trends, patterns, and insights relevant to financial markets, customer behavior, and business performance. Pre-process and clean large datasets to extract relevant features … complex datasets. Evaluate model performance and iterate on models to improve accuracy and efficiency, especially in the context of Gen AI technologies. Become a user of Symphony’s proprietary NLP software. Collaboration and Communication: Work closely with cross-functional teams, including software engineers, data engineers, and domain experts, to integrate AI models, particularly Gen AI models, into applications and systems. More ❯

on experience in developing and implementing AI and Data cloud solutions. Experience working with Azure AI services (or AWS, GCP) and AI model deployment. Understanding of generative AI, LLMs, NLP, and machine learning frameworks (TensorFlow, PyTorch, Hugging Face, etc.). Understanding of the AI application lifecycle, including application prototyping, productionising and monitoring. Python/Go/R. Problem solving skills. More ❯

workflows for data collection, analysis and reporting. Data analysis Analyse data trends, patterns and anomalies using statistical techniques to derive meaningful insights. Model development and evaluation Utilise machine learning, NLP, Generative AI, and other advanced statistical methods to build predictive and descriptive models. Validate and refine models to ensure accuracy and reliability. Reporting A proven track record of advanced dashboard More ❯

login/join with: Allianz have an exciting opportunity for a Senior Data Scientist to join the team in Guildford on a hybrid basis. As a Senior Data Scientist - NLP at Allianz Commercial, you will work closely with our team of data scientists, data engineers, ML engineers and analysts in designing and implementing solutions that extract insights from unstructured text … topic modelling and entity recognition to text generation and conversational AI. This role requires strong technical skills, a solid foundation in machine learning, and a passion for solving complex NLP problems. Salary Information Pay: Circa £75,000 per year. Pay is based on relevant experience, skills for the role, and location. Salary is only one part of our total reward … package. About You Research, design, and develop solutions using NLP models and algorithms to extract insights from unstructured text data. Collaborate closely with data engineers to pre-process and clean text data, ensuring data quality and compatibility with NLP models. Apply machine learning and deep learning techniques to tasks such as sentiment analysis, text classification, entity recognition, named entity recognition More ❯

or applied AI solutions. • A passion for Generative AI, and an understanding of strengths and weaknesses of Generative LLM's • Fundamental knowledge of ML, and basic knowledge of AI, NLP, and Large Language Models (LLM) • Comfortable working with Python and Jupyter Notebooks • Should have in-depth knowledge and familiarity with cloud platforms like Amazon Web Services (AWS), Google Cloud … Platform (GCP), and Microsoft Azure. Technical Skills – Good to have: • Expertise in any one framework (TensorFlow, Pytorch, Keras) • Experience in a statistical programming language (e.g. R or Python) and applied machine learning and AI techniques (i.e computer vision, deep learning, conversational AI, and natural language processing frameworks.) • Experience with Transforms Architecture Design, specializing LLM (Zero/… in conversational system architecture • Extensive knowledge on API’s & Integrations, Patterns. • Extensive knowledge of big data technologies • Knowledge on Statistical Methods • OTHER SKILLS WE'D APPRECIATE 1. Understanding of NLP engines, Artificial Intelligence, Machine Learning frameworks etc. EDUCATION QUALIFICATION • Graduate in Engineering OR master’s in computer applications. Process Skills: • General SDLC processes • Understanding of utilizing Agile and Scrum software More ❯

About the Role: Grade Level (for internal use): 10 Job Description The Role: Sr Data Scientist- NLP, LLM and GenAI S&P is a leader in risk management solutions leveraging automation and AI/ML. This role is a unique opportunity for hands-on ML scientists and NLP/Gen AI/LLM scientists to grow into the next step … in their career journey and apply her or his technical expertise in NLP, deep learning, GenAI, and LLMs to drive business value for multiple stakeholders while conducting cutting-edge applied research around LLMs, Gen AI, and related areas. Responsibilities: ML, Gen AI, NLP, LLM Model Development: Design and develop custom ML, Gen AI, NLP, LLM Models for batch and stream … processing-based AI ML pipelines. Model components will include data ingestion, preprocessing, search and retrieval, Retrieval Augmented Generation (RAG), NLP/LLM model development, fine-tuning and prompt engineering and ensure the solution meets all technical and business requirements. Work closely with other members of data science, MlOps, technology teams in the design, development, and implementation of the ML More ❯

datasets, deployment dates, and usage guidelines-promoting robust governance and transparency. Perform and guide model retraining, performance monitoring, and updates for complex production models (e.g., time series, anomaly detection, natural language processing, LLM-based text summarization), proactively addressing performance gaps. Collaborate closely with domain experts to capture critical business requirements, and lead efforts to gather, transform, and … prepare data for model training and deployment. Evaluate, implement, and refine state-of-the-art algorithms-including foundational language models, object detection/classification, and time series analysis-to tackle advanced enterprise challenges. Ensure strict adherence to enterprise standards for metadata management, governance, and security, integrating policy-as-code and compliance checks into the model lifecycle. Architect and refine … IAT Level II Certification may be required (GSEC, GICSP, CND, CySA+, Security+ CE, SSCP or CCNA-Security). Advanced proficiency in Python, SQL, PySpark, MLOps, computer vision, and NLP, Databricks, AWS, Data Connections Cluster Training and tools such as GitLab, with proven success in architecting complex AI/ML pipelines. Demonstrated ability to write clean, efficient code in Python and More ❯