276 to 300 of 4,521 Machine Learning Jobs in England

enjoy turning ambiguity into reliable production systems, you'll thrive here. Join a team that values craft, security, and learning. As an Applied AI ML Lead in LLM Suite Engineering, you will design and deliver production-grade AI/ML and agentic solutions that integrate seamlessly with existing systems. … algorithms that integrate with existing systems Create architecture and design artifacts for complex applications, ensuring design constraints are met through delivery Build AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworks Implement GenAI services leveraging Azure OpenAI ...

performance, scalability, and security. Participate in code reviews and provide constructive feedback to peers. Stay up to date with emerging Cloud and AI/ML technologies and industry trends to drive innovation and continuous improvement Lead communities of practice across Software Engineering to promote awareness and adoption … software engineering concepts and applied experience Experienced in cloud development (AWS), with a focus on application design and development. Experience with AI/ML model integration, Prompt engineering, LLM APIs (OpenAI, Bedrock) and Generative AI Advanced in Java and Python Strong experience with cloud platforms like AWS, Azure, or Google ...

enjoy turning ambiguity into reliable production systems, you’ll thrive here. Join a team that values craft, security, and learning.As an Applied AI ML Lead in LLM Suite Engineering, you will design and deliver production-grade AI/ML and agentic solutions that integrate seamlessly with existing systems. You will … maintain algorithms that integrate with existing systemsCreate architecture and design artifacts for complex applications, ensuring design constraints are met through deliveryBuild AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworksImplement GenAI services leveraging Azure OpenAI models ...

enjoy turning ambiguity into reliable production systems, you’ll thrive here. Join a team that values craft, security, and learning. As an Applied AI ML Lead in LLM Suite Engineering, you will design and deliver production-grade AI/ML and agentic solutions that integrate seamlessly with existing systems. … algorithms that integrate with existing systems Create architecture and design artifacts for complex applications, ensuring design constraints are met through delivery Build AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworks Implement GenAI services leveraging Azure OpenAI ...

build, and deploy scalable machine learning algorithms and software solutions. Analyse, cleanse, and normalise complex time-series data and dynamical systems. Integrate ML models into production using cloud platforms and modern JavaScript frameworks. Collaborate within an Agile environment to deliver robust data structures and algorithms. What … engineering and data science capabilities: Core Development: Proficiency in Python, JavaScript, and Java, alongside modern frameworks (React, Redux, Vue, or Angular). Data Science & ML: Solid understanding of common ML techniques, trade-offs, and scalable ML architecture (MapReduce, streaming). Data Expertise: Experience with time-series data, dynamical systems ...

test development, maintenance, and coverage. They combine deep QA automation expertise with practical experience using AI to enhance testing workflows. Experience testing AI/ML applications or validating machine learning models is an asset. Responsibilities Design and maintain automated test suites, evaluation scenarios, metrics, and test datasets … testing for AI services and backend systemsDefine quality strategy and acceptance criteria for AI-powered applications across functional, API, integration, and AI/ML featuresTest AI/ML applications and machine learning models from a product and user perspectiveEvaluate AI/ML model outputs for correctness, consistency ...

test development, maintenance, and coverage. They combine deep QA automation expertise with practical experience using AI to enhance testing workflows. Experience testing AI/ML applications or validating machine learning models is an asset. Responsibilities Design and maintain automated test suites, evaluation scenarios, metrics, and test datasets … testing for AI services and backend systemsDefine quality strategy and acceptance criteria for AI-powered applications across functional, API, integration, and AI/ML featuresTest AI/ML applications and machine learning models from a product and user perspectiveEvaluate AI/ML model outputs for correctness, consistency ...

cutting-edge analytics solutions? About our team: We are a fast-moving, high-impact Data Science & AI team building real-world GenAI and ML solutions across the entire LexisNexis business. Our work powers smarter decisions for Product, Sales, Finance, Marketing, Customer Success, and Engineering—everything from predictive models to enterprise … machine learning, analytics, data engineering, cloud platforms, and enterprise system integrations. In this role, you will design, build, and deploy AI and ML solutions that support key business functions across Product, Sales, Finance, Marketing, Customer Success, and Engineering. You will work end-to-end across ideation, modelling, experimentation ...

test development, maintenance, and coverage. They combine deep QA automation expertise with practical experience using AI to enhance testing workflows. Experience testing AI/ML applications or validating machine learning models is an asset. Responsibilities Design and maintain automated test suites, evaluation scenarios, metrics, and test datasets … testing for AI services and backend systemsDefine quality strategy and acceptance criteria for AI-powered applications across functional, API, integration, and AI/ML featuresTest AI/ML applications and machine learning models from a product and user perspectiveEvaluate AI/ML model outputs for correctness, consistency ...

About our team We are a fast-moving, high-impact Data Science & AI team building real-world GenAI and ML solutions across the entire LexisNexis business. Our work powers smarter decisions for Product, Sales, Finance, Marketing, Customer Success, and Engineering—from predictive models to enterprise GenAI apps to automation that … machine learning, analytics, data engineering, cloud platforms, and enterprise system integrations. In this role, you will design, build, and deploy AI and ML solutions that support key business functions across Product, Sales, Finance, Marketing, Customer Success, and Engineering. You will work end-to-end across ideation, modelling, experimentation ...

principles.You will also lead delivery across AI workstreams, mentor engineers, and support business development activities.Key ResponsibilitiesDesign, develop, and deploy production-grade AI and ML solutions, including GenAI and LLM-enabled systems.Shape AI solution architectures, selecting appropriate patterns (e.g. batch vs streaming, RAG, feature stores, model serving).Lead AI/ML … shaping solution options and delivery approaches.Build strong relationships with clients and partners, acting as a trusted technical advisor.Experience & Capability3+ years’ experience delivering AI and ML solutions in production environments.Demonstrated experience delivering GenAI and LLM-based solutions from prototype through to production.Strong Python engineering skills, with a focus on quality, testing ...

spirit, cohesion, and appreciation - And through our talented people, innovative culture, and technical and business expertise, we deliver game changing outcomes every day. Our learning culture and flat hierarchy are our recipes for success. But don't take our word for it - Have a look at what our employees … Analytics, and Azure Machine LearningImplement data pipelines and workflows to automate and operationalize machine learning solutions using tools such as Azure ML Pipelines, Azure DevOps.Run experiments and monitor performance of machine learning solutions using tools such as Azure Azure ML, and Azure Application Insights.Operationalise ...

defense safeguarding invaluable intellectual property while accelerating our innovation velocity.What you will doAdversarial Threat Modeling: Conduct cutting-edge threat modeling focused on AI/ML vulnerabilities, engineering a comprehensive risk management framework tailored to an AI-powered life sciences platform.Model Artifacts Protection: Partner with AI teams to establish a granular … inventory, classification and protection framework for ML models’ weights, code, and training data.Agentic AI & LLM Guardrails: Design and deploy scalable guardrails, robust sandboxing, and real-time monitoring controls for our extensive LLM ecosystem, including ADK, MCP, and autonomous agentic workflows.Collaborative Security Engineering: Partner with ML researchers and platform engineers ...

teamGenerative AI Innovation Center What is it A program that pairs you with AWS science and strategy experts with deep experience in AI/ML and generative AI techniques to:Imagine new applications of generative AI to address your needs.Identify new use cases based on business value.Integrate Generative AI into … internal/external stakeholders and Customers.- Ability to collaborate with global/enterprise account sales and delivery teams to drive adoption of AI/ML Solutions into top accounts.- Experience and passion for designing and developing innovative AI/ML solutions that leverage natural language processing, computer vision, statistical learning ...

Oncology Data Science team in Biomedical Research supports the Oncology Disease Area with computational biology, Artificial Intelligence/Machine Learning (AI/ML), and data engineering for novel therapeutics across multiple drug modalities. As integrated scientists and engineers, we apply advanced analytics to pre-clinical and clinical projects … stakeholders.Proven history of contributions to the scientific community in the form of papers and/or conference presentations.Preferred Requirements: Experience with AI/ML approaches specific to the low molecular weight field including computational chemistry and application of generative AI in chemistry.Experience with cell line profiling, shRNA or CRISPR perturbation ...

impact. Independently replicate the model development process where necessary and conduct challenger analyses. Collaborate closely with first-line data scientists, machine learning (ML) engineers, and product stakeholders to understand models’ business context and ensure transparent communication of model risks and validation findings. Provide actionable recommendations and formally document … review, surfacing cross-source inconsistencies, streamlining challenger analysis, etc. Stay up-to-date with emerging trends in credit and finance modelling and AI/ML technologies. Maintain robust model risk management frameworks, policies, and procedures in line with evolving regulatory expectations and industry best practices. Who you are Advanced degree ...

between traditional predictive algorithms and modern generative systems. Your Impact Advanced Modeling & Predictive Analytics: Lead the research, design, and implementation of advanced Machine Learning, Deep Learning, and Timeseries Forecasting models to solve complex enterprise business and planning challenges. Generative AI Architecture: Architect GenAI solutions, focusing on fine … Familiarity with Anaplan or similar enterprise planning platforms. Experience with A/B testing and experimentation frameworks for AI features. Contributions to open‐source ML projects or research publications. Our Commitment to Diversity, Equity, Inclusion, and Belonging (DEIB) We believe at Anaplan that diversity, equity, inclusion and belonging are central ...

safer medicines for millions of patients worldwide? As a Senior Expert I or Senior Expert II Data Science, you will apply advanced artificial intelligence, machine learning, and computational modelling to tackle complex scientific challenges and influence critical decisions across drug discovery and early development. Working within a highly … Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Python (Programming Language), Stakeholder Engagement, Statistical Analysis, Time Series AnalysisSummaryLocation: Cambridge (USA)Type: Full time ...

Senior MLopsLocation: AmsterdamAbout our TeamData 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 Role:Join the team that powers Elsevier’s Data Scientists at Corporate … APIs such as OpenAI) Maintain and version model registries and artifact stores to ensure reproducibility and governance Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS Sagemaker , MLflow, Azure ML. ...

threats. The organisation combines cybersecurity expertise, proprietary solutions, and technology partnerships to deliver tailored security services across various sectors. The organisation is seeking an ML Research Engineer to join its Innovation & Research team and help develop AI-powered security operations capabilities. This role focuses on building and evaluating … agentic systems, improving machine learning models and workflows, analysing performance, and researching security challenges such as adversarial attacks and offers the opportunity to work on cutting-edge AI technologies, influence product development, and collaborate with researchers, engineers, and security specialists. Responsibilities Designing and building evaluation frameworks ...

unsupervised learning, deep learning, transformers, generative AI and agentic AI patterns.Ability to assess the suitability, limitations and risks of different AI/ML techniques for real client use cases.Experience working across at least part of the data science or machine learning lifecycle, from exploration and prototyping … across all the areas below, but we are particularly interested in people who can bring in one or more of them:Applying AI/ML techniques to text, audio, imagery, video, geospatial, graph or multimodal data.Developing solutions using machine learning frameworks such as PyTorch, TensorFlow, scikit-learn ...

unsupervised learning, deep learning, transformers, generative AI and agentic AI patterns.Ability to assess the suitability, limitations and risks of different AI/ML techniques for real client use cases.Experience working across at least part of the data science or machine learning lifecycle, from exploration and prototyping … across all the areas below, but we are particularly interested in people who can bring in one or more of them:Applying AI/ML techniques to text, audio, imagery, video, geospatial, graph or multimodal data.Developing solutions using machine learning frameworks such as PyTorch, TensorFlow, scikit-learn ...

unsupervised learning, deep learning, transformers, generative AI and agentic AI patterns.Ability to assess the suitability, limitations and risks of different AI/ML techniques for real client use cases.Experience working across at least part of the data science or machine learning lifecycle, from exploration and prototyping … across all the areas below, but we are particularly interested in people who can bring in one or more of them:Applying AI/ML techniques to text, audio, imagery, video, geospatial, graph or multimodal data.Developing solutions using machine learning frameworks such as PyTorch, TensorFlow, scikit-learn ...

driven engineering practices, fostering a culture of continuous learning and experimentationPartner with Architecture and Data Science teams to define best practices for ML model deployment, data pipeline design, and cloud infrastructure standardsConduct thorough code reviews with a focus on AI-assisted quality, providing constructive feedback to enhance code quality … fundamentally enhance how software is designed, built, tested, and deployedHands-on experience with machine learning concepts and the ability to integrate ML models into production applications and data pipelinesProficiency with Snowflake for data warehousing, analytics, and building scalable data platformsExperience designing and building event streaming architectures using technologies ...

advanced algorithms and training techniques for Large Language Models (LLMs). LLM Training (Continued pretraining, instruction tuning, reinforcement learning, distributed training, efficient ML techniques) Post-training techniques for planning, reasoning & complex workflows (e.g., reasoning models, LLMs + knowledge graphs, test time compute, CoT pipelines, tool use & API calling, etc. … demonstrated experience successfully managing software development teams in an agile environment. Experience spearheading technical development in a cross-functional setting, with responsibility for ML applications; close partnership with Applied Scientists, R&D groups, or similar. A portfolio showcasing significant contributions to technology innovation Excellent project management, organization and communication skills ...