251 to 275 of 3,473 Machine Learning Jobs in London

ReqID: FEQ327R328Recruiter: Kanwal MatharuLocation: London, United Kingdom - HybridSkills: Data Science, Machine Learning, AI, LLM, GenAIAs a Senior Specialist Solutions Engineer (SSE), ML Engineering, you will be the trusted technical ML expert to both Databricks customers and the Field Engineering organisation. You will work with Solution Architects to guide … customers in architecting production-grade ML applications on Databricks, while aligning their technical roadmap with the evolving Databricks Data Intelligence Platform. You will continue to strengthen your technical skills through applying the latest technologies in GenAI, LLMOps, and ML, while expanding your impact through mentorship and establishing yourself ...

innovation in this fast evolving space as new technologies reshape how money moves. In this role, you will work at the forefront of modern machine learning and generative AI to deliver meaningful, lasting impact on global finance. You will partner closely with product, operations, risk, and technology teams … into measurable outcomes. You will also have opportunities to mentor others and help shape how we build and operate production AI.As a Vice President Machine Learning Data Scientist in Payments Machine Learning, you will lead the design, development, and production deployment of machine learning ...

ReqID:FEQ327R501Location: LondonSkills: Data Science, Machine Learning, AI, LLM, GenAIMissionAs a Senior Specialist Solutions Architect (ML & AI), you will serve as the trusted technical ML and AI expert for Databricks customers and the Field Engineering organization. You will partner with Solution Architects to guide enterprise and strategic customers … architecting production-grade ML and AI applications on the Databricks Data Intelligence Platform. You will also continue to sharpen your technical expertise in cutting-edge areas like GenAI, ML, MLOps, and LLMOps, while mentoring colleagues and establishing yourself as an AI thought leader.Impact you will haveArchitecting Workloads: Design and implement ...

collaborate in person.Our Data EnvironmentOur Data teams are aligned to divisions covering the following Banking Services & Products, Customer Identity & Financial Crime and Data & ML Engineering. Our Data teams are excited about delivering meaningful and impactful insights to both the business and more importantly our customers. Hear from the team … multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good.About the RoleThe ML Projects team is at the forefront of bringing cutting edge machine learning to the core of what we do at Starling. ...

here. Everything that makes you unique is welcome; join us and let’s build what’s next - together! Role Overview We are seeking a ML Ops Engineer to join our Platform Engineering team at Anaplan. In this role, you will design, scale, and maintain high-performance MLOps and LLMOps infrastructure … supporting our cutting-edge AI-infused scenario planning platform. You will work closely with Data Scientists, ML Engineers, and Cloud Infrastructure teams to streamline model training, deployment, and inference while ensuring optimal GPU utilisation, reliability, and cost-efficiency. Your Impact Provision and manage cloud-native AI/ML infrastructure utilising ...

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 ...

deployment within cloud-based environments Maintain high standards of code quality, documentation, and testing within a DevOps-oriented workflow Apply strong knowledge of ML techniques, from supervised/unsupervised learning through to emerging methods in generative ai and large language models What We’re Looking For: Essential Skills & Experience … across varied data types and business domains Familiarity with DevOps practices and tools such as Git Cloud experience (e.g., Azure, AWS) and working with ML platforms and services Excellent communication skills, with the ability to explain complex concepts to non-technical stakeholders Ability to align analytical outputs with broader business ...

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 ...

data science, contributing expertise across projects, bids and stakeholder discussions Leading and delivering complex machine learning and AI projects in collaboration with ML engineers, delivery teams and customers Engaging with users to define requirements, scope AI use cases and develop realistic delivery plans Supporting the design, development … tabular data Strong Python skills and experience with common libraries (e.g. pandas, NumPy, scikit-learn, PyTorch, Transformers, statsmodels, PyMC) Understanding of software engineering and ML best practices, including version control, packaging and model deployment Experience training and deploying models using cloud platforms, particularly AWS Ability to communicate complex ideas clearly ...

effective AI solutions. This is a hands-on technical leadership role, ideal for someone currently operating as a Lead AI Architect, Principal AI/ML Engineer, AI Engineering Lead, Principal Architect, AI Practice Lead or similar , and looking to take the next step into an Associate Director-level position. … public sector environments. Lead the development and deployment of production-grade Generative AI and Machine Learning solutions. Architect systems integrating LLMs and ML models into wider enterprise applications and workflows. Oversee the full technical lifecycle, from solution design and model selection through to deployment, monitoring and continuous improvement. ...

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 ...

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 workstreams end-to-end, including planning, delivery governance, and stakeholder management. Mentor and support AI engineers, data scientists, and software engineers, fostering high engineering standards and collaboration. Implement secure, scalable deployment patterns aligned with governance, compliance, and Responsible AI expectations. Embed monitoring, evaluation, and continuous improvement across AI solutions. ...

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 ...

build production‐ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills. Your Impact Lead the architecture, design, and deployment of scalable Generative AI and Machine learning systems into production environments. … production environments Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour Collaborate with data scientists to productionise ML models and forecasting algorithms Your Skills Extensive hands‐on professional experience in the field of Artificial Intelligence, Machine Learning, or related engineering domains. ...

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 ...

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 ...

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. ...

interpretation, validation and communication of innovative exploratory analyses and algorithms, to facilitate internal decision makingYou will provide technical expertise in data science and (predictive) machine learning/AI to identify opportunities for influencing internal decision making as well as discussions on white papers/regulatory policy.You will perform … 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: London (The Westworks)Type: Full time ...

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 ...

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 ...

AECOM’s commitment to delivering sustainable and innovative solutions, the Senior Data Scientist will play a critical role in advancing analytics, AI/ML strategies, and IoT-driven insights to unlock measurable business value across infrastructure, environmental, and urban development sectors.Reporting to the Data Intelligence Lead, this role will focus … designing and implementing predictive and prescriptive models, driving AI/ML strategies, and collaborating with cross-functional teams to integrate data science solutions into AECOM’s operational workflows. The ideal candidate will bring expertise in advanced analytics, machine learning, and IoT technologies, with a passion for solving complex ...

governance frameworks. You will ensure that data from various sources is well-organised, accessible, and AI-ready, working closely with data engineers and ML engineers to build robust data pipelines and maintain high data quality for analytics and model development.ResponsibilitiesData Modelling & Schema Design: Develop and maintain data models (conceptual, logical … support model interpretability and enable troubleshooting of data issues, which is critical in AI development.Collaboration with Engineering Teams: Work closely with data engineers, ML engineers, and data scientists to ensure the data architecture meets their needs. You will collaborate on designing data interfaces (e.g. APIs or query endpoints) and assist ...