901 to 925 of 4,926 Machine Learning Jobs in England

responsible AI solutions across a range of high-profile client engagements. Key responsibilities will include: * Designing and implementing end-to-end AI/ML solutions from development through to deployment and monitoring * Building scalable Generative AI and Agentic AI solutions, including RAG pipelines and orchestration frameworks * Implementing MLOps frameworks, governance … major Consulting firm, and/or in industry * A strong consulting mindset with experience engaging senior stakeholders * Proven experience designing and delivering AI/ML solutions at scale * Strong understanding of Generative AI, Agentic AI and modern AI engineering frameworks * Experience with at least one major cloud platform including Azure ...

Years of professional experience building and deploying machine learning or AI systems in production; Proficiency in Python and experience with AI/ML frameworks such as PyTorch, TensorFlow, or JAX; Strong foundation in machine learning, deep learning architectures, and natural language processing, particularly large language … leave for all parents; Fertility and family planning support; Early-detection cancer testing through Galleri; Competitive pension scheme and company contribution; Annual wellness and learning and development stipends; Company-wide and team off-sites; Competitive compensation and company stock options. #J-18808-Ljbffr ...

distinctive capabilities, models, and insights through your work with client teams and clients. You will ensure statistical validity and outputs of analytics, AI/ML models and translate results for senior stakeholders, and will write optimized code to advance our Data Science Toolbox and codify analytical methodologies for future deployment. … e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf/keras, langchain). R and C++ optional. Experience with version control (GitHub) ML experience with causality, Bayesian statistics & optimization, survival analysis, design of experiments, longitudinal analysis, surrogate models, transformers, Knowledge Graphs, Agents, Graph NNs, Deep Learning, computer ...

operational users to develop and deploy analytics solutions that enable insight and mission advantage. Typical engagements include: Intelligence data exploitation and advanced analytics ML model development and optimisation Natural Language Processing (NLP), data matching and pattern detection Data triage and automated analysis of large datasets Operational decision-support systems … deploy AI and machine learning solutions to analyse complex structured and unstructured data. Build and maintain scalable data and AI/ML pipelines to support advanced analytics and automated insight generation. Apply a range of data science techniques including machine learning, statistical modelling, deep learning ...

operational users to develop and deploy analytics solutions that enable insight and mission advantage. Typical engagements include: Intelligence data exploitation and advanced analytics ML model development and optimisation Natural Language Processing (NLP), data matching and pattern detection Data triage and automated analysis of large datasets Operational decision-support systems … deploy AI and machine learning solutions to analyse complex structured and unstructured data. Build and maintain scalable data and AI/ML pipelines to support advanced analytics and automated insight generation. Apply a range of data science techniques including machine learning, statistical modelling, deep learning ...

team partners closely with trading, technology, and risk teams to deliver impactful tools and analytics. The team specializes in building models that leverage Machine Learning, Statistics, and Operations Research to solve complex business challenges. As a Vice President in QTR Prime Finance, you will collaborate with senior stakeholders … Document models, methodologies, and processes for transparency and knowledge sharing. Required Qualifications, Capabilities and Skills Advanced degree (Masters or PhD) in Statistics, AI/ML, Computer Science, Operations Research, or related quantitative field. Significant experience in quantitative modelling, analytics, or related roles. Strong background in AI, machine learning ...

into AI-driven solutions Support pre‐sales activities, including client workshops, technical presentations, solution scoping and proposal development Evaluate and select appropriate AI/ML and agent frameworks, tools and platforms to meet project requirements Guide teams in best practices for model development, deployment and monitoring in production environments Ensure … solutions are scalable, secure and compliant with industry standards Mentor and support engineering teams in AI/ML methodologies and technologies Stay current with the latest advancements in AI, GenAI and cloud technologies Contribute to proposals, client presentations and thought leadership within the AI domain Partner with sales and account ...

deliver even smarter insights to our teams across the organisation. About the role As a Data Scientist, you’ll be responsible for developing machine learning models and designing AI‐driven workflows to process and extract value from data. You’ll also create reusable features using SQL and Python … reporting infrastructure. Your day‐to‐day responsibilities will include: Developing, testing and deploying predictive machine learning models within Azure (e.g., Azure ML, Azure AI Foundry). Monitoring and evaluating model performance, implementing iterative improvements and retraining where required. Designing and implementing AI‐driven workflows to analyse data ...

other quantitative methods to support the Commercial and Investment Bank (CIB). The QTR Securities Services and Payments team applies cutting-edge AI/ML techniques to fundamentally transform the way we do business by enabling business revenue growth and efficiency within the CIB organization. Job Summary As an Associate … support the business in tackling their most technically complex business problems to optimize revenue and manage risks. This could range from developing AI/ML applications that make business-critical predictions such as client pricing, to handling vast data sets using the J.P.Morgan's Cloud capabilities or optimal hedging policies ...

About our Team Data Science Life Sciences is a diverse team focusing on GenAI, ML, NLP. We mainly develop best-in-class enrichment pipelines for Elsevier’s life science .com products such as Reaxys, Embase and Pharmapendium. About the Role As Principal Data Scientist (AI/NLP & Generative … involvement will be occasional, on high priority or high risk work. Responsibilities Technical Direction & Oversight Set technical direction and architectural standards for AI/ML, NLP, and generative AI solutions across teams, including LLM powered workflows, RAG systems, retrieval, ranking, and recommendation capabilities. Guide how scientific metadata, ontologies, taxonomies ...

Data team, working within Risk & Fraud. The brief is simple: reduce fraud without adding friction for good users. In practice that means ML models, deterministic rules and signal tuning, and working directly with our external risk vendors. You own that work end to end, from the question, to what ships … analyze A/B and multivariate experiments, identify conversion bottlenecks (KYC, payment method, geo), and partner with PMs and designers to ship measurable improvements. ML/AI modeling. Design, train, and deploy machine learning models, from classification and forecasting to clustering and recommendation, that power decisions inside ...

scalable, secure, and reliable machine learning services while driving innovation and operational excellence. Responsibilities Lead and grow a team of full-stack ML engineers, QA engineers, and a UI developer. Define technical direction for AI-enhanced services, internal tools, and platform components. Drive architecture for model deployment pipelines … inference APIs, and data and feature systems. Ensure high-quality delivery across code quality, testing, documentation, and observability. Partner with Product, Architecture, and ML Research teams to prioritise and scope work. Foster a culture of modern AI development practices, including LLM tooling, MLOps, and automation. Set and enforce DevOps ...

within the Aerodynamics department. Reporting to the Lead AI Engineer, you will work on specialist projects that bridge aerodynamic engineering and AI — developing advanced machine learning models, surrogate models, and automated geometry tools that give Williams Racing a competitive edge in vehicle development. This is a technically demanding … aerodynamic applications. Identify AI-driven opportunities to improve aerodynamic development efficiency within cost cap requirements. Qualifications Proven experience developing and deploying AI/ML models, particularly for scientific or engineering applications. Strong proficiency in Python with the PyTorch framework. Understanding of computational geometry principles and familiarity with mesh generation algorithms. ...

Worldwide Field Operations (WWFO) team is looking for a Solution Architect with expertise in Generative AI, Data Science applications and Machine Learning (ML) to work with our Hyperscaler partners. In our Solutions Architecture team, we work with the most exciting platform for accelerated computing and drive the latest … Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields A proven track record of academic and/or industry experience in fields related to machine learning, deep learning and/or data science You are excited to work with multiple levels and teams across organizations (Engineering, Product ...

match the full criteria, so if you have most of the below, we’d like to hear from you: Significant experience applying data science, machine learning, statistical modelling or advanced analytics to complex real‐world datasets. Strong applied statistical expertise, including the ability to quantify risk and uncertainty … epidemiology, operational research, or cyber risk. Familiarity with UK data protection, research governance or health data access expectations. Experience with PETs or privacy‐preserving ML frameworks such as Flower, Opacus, TensorFlow Federated or similar. Cloud platforms, containerisation, CI/CD, MLOps or production ML systems. Experience evaluating synthetic data using ...

About our Team Data Science Life Sciences is a diverse team focusing on GenAI, ML, NLP. We mainly develop best-in-class enrichment pipelines for Elsevier’s life science .com products such as Reaxys, Embase and Pharmapendium. About the Role As Principal Data Scientist (AI/NLP & Generative … involvement will be occasional, on high priority or high risk work. Responsibilities Technical Direction & Oversight Set technical direction and architectural standards for AI/ML, NLP, and generative AI solutions across teams, including LLM powered workflows, RAG systems, retrieval, ranking, and recommendation capabilities. Guide how scientific metadata, ontologies, taxonomies ...

deploy and operate production-grade machine learning platforms using the AWS SageMaker MLOps framework. This role focuses on enabling the full ML lifecycle- data preparation, model deployment, monitoring, and retraining-through standardised, automated, and governed pipelines. You will work at the intersection of data science, cloud engineering … scale, monitored for drift and performance, and governed in line with enterprise and regulatory expectations. You will play a key role in standardising ML lifecycle practices, automating pipelines, and embedding operational excellence, security, and cost efficiency into AI/ML workloads. What you’ll be doing SageMaker Pipelines for training ...

apply your skills and passion for technology at Thomson Reuters Labs. We are seeking a Research Engineer who will bring expertise in AI and ML and is interested in building data-driven capabilities that transform the way legal, accounting, and government professionals work across the globe. As a member … modern software development practices, you will be involved in the entire software development lifecycle, designing, building, testing and delivering high-quality solutions. Build Scalable ML Solutions:You will create large scale data processing pipelines to help researchers build and train novel machine learning algorithms. You willdevelophigh performing scalablesystems ...

over EVM (and other) blockchain data to attribute on‐chain activity and uncover new insights. Apply advanced techniques including graph computation, statistical modeling, and machine learning to large‐scale on‐chain datasets. Identify and resolve inefficiencies in code, methodology, and workflows; ensure your work integrates cleanly into … Python and SQL, with a track record of writing clean, testable, production‐quality code. Demonstrated experience applying advanced analytical techniques (e.g. graph algorithms, ML, statistical inference) to large, messy datasets. Comfort working with EVM‐based blockchain data, or strong evidence of the aptitude to ramp up quickly on EVM data ...

experience building and deploying machine learning or AI systems in a production environment. Proficiency in Python and experience with relevant AI/ML frameworks such as PyTorch, TensorFlow, or JAX. A strong foundation in machine learning principles, deep learning architectures, and natural language processing, particularly … testing through Galleri Competitive pension scheme and company contribution Annual work-life stipends for: Wellness stipend for gym, massage/chiropractor, personal training, etc. Learning and development stipend Company-wide off-sites and team off-sites Competitive compensation and company stock options #J-18808-Ljbffr ...

recommendations, digital experiences, communications. And we aim to achieve this using our incredible data asset, our rich customer understanding, and state of the art machine learning and AI. This role will work in a team dedicated to personalising customer experiences within the Nectar loyalty programme and optimising large … environment. Solid understanding of working with production codebases, such as version control, CI/CD, and batch processing. Practical experience working on cloud-based ML platforms. Development and coaching A strong awareness and understanding of technology trends and direction in Data Science, analytics and AI. Ability to support ...

business challenges across customer behaviour, risk, and pricing. What You'll Do · Build End-to-End Solutions: Scope, design, train, and deploy production-ready ML models and statistical experiments. · Shape the Platform: Collaborate with Data Engineering and Analytics to build reproducible pipelines and integrate workloads into a Unified, AI-powered … Excellence: Monitor live model performance, guard against data drift, and champion best practices in MLOps. What You Bring ·Proven experience building and iterating on ML models in a commercial setting. ·Expert-level Python skills (pandas, NumPy, scikit-learn, etc.) and strong statistical grounding. ·Experience working within cloud or modern data ...

Responsibilities Design, build, and optimise data pipelines using dbt, Python, and SQL Implement and maintain scalable ELT/ETL frameworks that power analytics and ML systems Collaborate with Data Science and Platform teams to ensure robust and reliable model deployment pipelines Own the reliability, scalability, and observability of data workflows … production Contribute to data architecture decisions and documentation , ensuring data integrity and consistency across sources Design and maintain data models used by ML Engineers, Data Analysts, and Data Scientists Drive automation, versioning, and quality validation in data delivery Conduct exploratory data analysis to uncover trends and inform strategic decision-making ...

Digital Humans in complex scenarios. By providing instant feedback anytime, anywhere, we support individuals to thrive in real-world settings, while hospitals accelerate staff learning curves to eradicate errors and inequalities in patient care. First founded by a medical doctor and PhD in Artificial Intelligence, Re:course are proud … frameworks and their ecosystems such as Celery and others. Understanding of data streaming and messaging frameworks Experience with building scalable machine learning (ML) infrastructures, MLOps tools and techniques to deploy, monitor, and manage continuous model deployment pipelines Experience with infrastructure automation tools such as Terraform About you Want ...

teams to integrate AI solutions into business processes. Present research outcomes to stakeholders and at industry conferences. Stay current with advancements in AI and machine learning. Foster a culture of innovation and continuous improvement within the team. Required Qualifications, Capabilities, and Skills: Ph.D. in computer science, machine learning … Master’s degree with equivalent applied research and engineering experience plus 4 years of industry experience. Ability to build and ship AI/ML systems, ideally involving LLMs. Proficiency in Python and modern ML frameworks such as PyTorch or JAX. Hands-on experience across the LLM lifecycle, including fine-tuning ...