376 to 400 of 2,929 Machine Learning Jobs in London

customer outcomes, and build products that customers trust and love. The rapid pace of change within fintech creates exciting opportunities to apply advanced analytics, machine learning, and experimentation to real business challenges. As a Data Scientist, you will play a key role in helping Kroo use data more … operational efficiency, helping the business make informed decisions through robust analysis, experimentation, and modelling. How you'll contribute: Build and iterate on statistical and machine learning models to solve business problems across areas such as credit risk, fraud, customer engagement, and operational efficiency. Partner with stakeholders to define ...

role will architect and scale the systems that power our AI products, from real-time data pipelines and analytics infrastructure to vector databases and machine learning data workflows. You will work closely with AI engineers, backend engineers, and product teams to ensure our platform can process large volumes … architectures for operational and AI workloads. Develop and manage batch and real-time data pipelines. Build and optimise systems for vector search, retrieval and machine learning data pipelines. Ensure data reliability, security and governance across the platform. Collaborate with AI and backend engineering teams to support training, inference ...

outcomes, including resolution quality, customer effort, process adherence, consistency, fairness, durability of resolution and cost effectiveness. Identify the root causes of issues by combining machine learning, statistical methods and domain expertise from colleagues to understand what genuinely drives customer outcomes. Identify and test solutions Turn analytical insight into … analysis (e.g., classical ANOVA, non-parametric uncertainty quantification, Bayesian estimation) and causal inference, with experience designing both controlled experiments and observational studies. Experience applying machine learning, statistical modelling, NLP and LLM-based techniques to analyse customer behaviour and conversational data, diagnose root causes and identify the drivers ...

Role As a Senior Python Engineer, you will join our Data Science Products team to build robust backend systems and infrastructure for our machine learning products. This team ingests billions of complex sensor data points daily to produce advanced products that help millions of drivers park or charge … supportive environment. How to make an impact Deliver high-performance APIs with a focus on speed and reliability, utilizing FastAPI to serve machine learning insights. Deploy and manage cloud-native services using strong AWS knowledge and Infrastructure as Code (IaC) principles. Leverage Kafka to deliver near real time ...

authoritative technical foundation for our curriculum and training programmes. The Technical Writer will work closely with the curriculum lead, who will continue to own learning architecture, exercises, assessments, trainer materials, and broader adoption initiatives. Many customers do not have in house specialist knowledge in all areas of our platform … capabilities, so the documentation must enable technically literate users to complete appropriate machine learning and simulation workflows independently. Guides should evolve with every platform release, and should be scoped starting at the engineering level and carried through to clear, customer facing guides. Early priorities include plugging existing gaps ...

FinTech with an innovative approach to lending. You'll play a key role in building and improving fraud prevention capabilities, working on high-impact machine learning projects that directly influence customer outcomes, risk strategy, and business performance. THE COMPANY Our client is a forward-thinking FinTech with … fraud detection, identity verification, and fraud scoring models * Analyse large and complex datasets to identify fraud trends, risks, and opportunities * Evaluate new data sources, machine learning techniques, and fraud prevention tools * Build monitoring and reporting solutions to track model and fraud performance * Collaborate with Product, Engineering, Risk ...

through its membership of Oaklins. Cavendish plc is listed on AIM. Job Overview This role is within the Business Intelligence function focussed on leveraging machine-learning tools and techniques to augment both our business development capability and our broader data and analytics framework. You will be working closely … tasks based on technical feasibility, implementation complexity, and business impact. Design and implement robust and efficient data management processes. Design, implement and finetune machine learning algorithms and models. Collaborate with business intelligence and IT colleagues on engineering solutions. Develop and regularly present to management on the “AI roadmap ...

pace and become job-ready in as little as a few weeks. Our programme includes: Official AWS Certified Cloud Practitioner certification Training in Python, Machine Learning, and AI systems Hands-on projects using real-world AI tools and technologies Professional CV and LinkedIn support Interview preparation Dedicated recruitment … cost of your training over 12 months so you can get qualified without financial pressure. Salary expectations: AI Engineer: £45,000 £60,000 Machine Learning Engineer: £60,000 £75,000 Progression into senior AI roles with higher earning potential We support you into employment We focus on outcomes ...

experience Career Level: Associate Director Role Overview The AI & Spatial Intelligence Lead shapes and delivers AI-first solutions that combine data engineering, advanced analytics, machine learning, and intelligent agents with enterprise geospatial platforms. The role turns complex spatial, asset, operational, and external data into trusted decisions and automated … products and scalable pipelines that integrate geospatial, asset, operational, imagery, IoT, and enterprise data across cloud and edge environments. Analytics & AI Apply spatial analytics, machine learning, computer vision, optimisation, knowledge graphs, and digital twins to predict risk, identify patterns, and improve decisions. Agents & automation Create AI agents ...

evaluate emerging technologies that can deliver measurable business outcomes. The successful candidate will combine strong data science expertise with hands-on experience across machine learning, Generative AI and Large Language Models (LLMs). You will work closely with multidisciplinary teams to rapidly assess ideas, develop proofs of concept … discovery, research and feasibility assessments. Analyse data sets, business processes and operational challenges to identify opportunities for AI adoption. Develop, test and evaluate machine learning and Generative AI prototypes. Design evaluation frameworks and performance benchmarks for AI solutions. Produce clear technical findings, insights and recommendations. Collaborate with engineers ...

organisation's data platform, including data warehouses, lakehouses, master data management solutions, and API frameworks Design the data foundations required to support AI and machine learning initiatives, ensuring high-quality, trusted, and accessible data. Partner with Data Engineering, Data Governance, and Analytics teams to ensure architecture standards … Data Mesh concepts API-led architectures Event-driven integration patterns Experience architecting solutions that support both operational reporting and advanced analytics, including AI and machine learning workloads. Strong knowledge of Azure-based data platforms and cloud architecture principles. Familiarity with Master Data Management (MDM) frameworks and technologies. Experience ...

client is a leading British bank. Join us at our client as an Integrated Financial Crime Model Developer. You will design, build and deploy machine learning models that support scalable, high quality financial crime detection across the bank. You will work within the Integrated Financial Crime portfolio … robustness, accuracy and performance of existing models. To be successful in this role, you will have experience in the following areas: Strong experience in machine learning and advanced analytics. Advanced Python skills for data processing and model development. Proven experience working with Databricks. Solid software engineering practices, including ...

client is a leading British bank. Join us at our client as an Integrated Financial Crime Model Developer. You will design, build and deploy machine learning models that support scalable, high quality financial crime detection across the bank. You will work within the Integrated Financial Crime portfolio … robustness, accuracy and performance of existing models. To be successful in this role, you will have experience in the following areas: Strong experience in machine learning and advanced analytics. Advanced Python skills for data processing and model development. Proven experience working with Databricks. Solid software engineering practices, including ...

software package proficiencies, are required. Join us at our client as an Integrated Financial Crime Model Developer. You will design, build and deploy machine learning models that support scalable, high quality financial crime detection across the bank. You will work within the Integrated Financial Crime portfolio, a large … robustness, accuracy and performance of existing models. To be successful in this role, you will have experience in the following areas: • Strong experience in machine learning and advanced analytics. • Advanced Python skills for data processing and model development. • Proven experience working with Databricks. • Solid software engineering practices, including ...

build align with their teams' patterns. Over time, you’ll rotate into other areas of the team's work, including productionizing and maintaining machine learning pipelines. Key Responsibilities Help build the game event data hub and ingest data from multiple studios. Develop and orchestrate data ingestion, preparation, quality … data assets need attention. Coordinate changes with studio data engineers to keep shared solutions aligned with their needs and patterns. Contribute to productionizing machine learning pipelines, monitoring them and making fixes as you rotate across the team's responsibilities. Required Skills, Knowledge and Expertise Experience building and operating ...

organization scales. Ensure effective collaboration across AI engineering and deployment engineering teams. Technical Leadership Provide technical leadership and judgment across AI engineering, machine learning, deployment, and production infrastructure . Engage substantively with technical leaders across both AI development and production systems. Help shape the technical organization required … Preferred Qualifications Experience at a company of comparable scale during Series D or Series E , ... Experience building engineering organizations spanning AI research, applied machine learning, and production deployment . Experience as a founding or early engineering leader who successfully transitioned an organization from an early-stage team ...

simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days. Ki is proudly the biggest global algorithmic insurance carrier. … Understanding of infrastructure as code using tools such as Terraform. Data & Algorithms: Intermediate understanding of the control, management, and lifecycle of data products and machine learning algorithms. Industry Knowledge & Compliance: Understanding of the importance of market compliance and core regulatory requirements within the insurance space. Communication Skills: Highly ...

encompasses the products and systems closest to the customer journey - search, pricing, payments, fare intelligence, and conversational interfaces. You will define and lead the ML strategy, team, and delivery across this domain. That means building and scaling ML and AI capabilities that measurably improve the customer experience and drive business … outcomes. The work spans traditional ML systems and emerging agentic/LLM-based capabilities. You will lead multiple ML teams through their respective team leads, reporting to the Director of AI & ML. You’ll be accountable for the people (2 ML Managers and ~10 ICs), delivery, and budget across your ...

Enterprise Architect — Artificial Intelligence AI/ML Infrastructure, Platform & Governance Role Summary World Wide Technology is looking for a deeply technical Enterprise Architect who will own the delivery of AI projects end to end from the silicon and data center design that underpins AI workloads, through the software and MLOps … while mentoring delivery teams and shaping WWT's broader AI point of view. Key Responsibilities Own end-to-end technical delivery of AI/ML engagements: architecture definition, design authority, build oversight, and go-live validation. Host and chair Architecture Review Board (ARB) and Technical Design Authority (TDA) sessions ...

with product, data science, and core infrastructure teams to optimize GPU compute utilization, resolve cross‐boundary platform incidents, and mentor engineers on production‐grade ML practices. Who You Are 5–6+ years of professional experience in MLOps, ML platform engineering, ML infrastructure, or SRE/DevOps for production machine learning systems. Proven experience building, operating, and automating production ML pipelines covering experiment tracking, model registries, artifact versioning, dataset management, and deployment workflows. Deep hands‐on experience implementing observability for ML systems, including monitoring inference availability, latency, throughput, GPU/resource utilization, and data or model drift. Strong ...

delivery team. Experience of applying knowledge of cloud computing, including architecting and deploying solutions, and selecting appropriate tools and design patterns. Exposure to advanced machine learning techniques (e.g. reinforcement learning, deep learning). Experience owning the day-to-day resource allocation of a large team … external clients and partners within the public sector for successful technical delivery and to build strong long-term relationships Knowledge of data science and machine learning concepts and principles. Expertise in Python and SQL, both for development and to review code. Strong working knowledge of database systems (e.g. ...

serving it in production.You'll translate research decisions — architecture choices, tokenisation trade-offs — into production systems that set the direction for how other Klarna machine learning teams work.You'll evaluate the customer representations the model produces against real underwriting outcomes, not just training-loss metrics.Who you areYou understand … playbook yet.Bonus points forYou've optimised GPU-level performance or written Triton kernels.You have machine learning experience outside deep learning — classical ML, statistics, or other modelling approaches.You've worked with large-scale transactional or financial data before.You've worked in ML infrastructure or MLOps.You hold ...

About the role The AI & ML Engineering team accelerates the adoption of AI across the business, championing innovation while ensuring our machine learning solutions are robust, scalable, and cost-efficient. We enable teams to solve problems using existing AI tools where possible and build custom solutions when needed. … remit spans AI enablement, agentic systems development, and “conventional” ML engineering for non-GenAI applications e.g. recommender systems, forecasting models, and more. We’re looking for an AI & ML Engineer who is passionate about building production‐ready AI and machine learning solutions. You'll work across a variety ...

Snap Inc. is seeking a Machine Learning Engineer to build and deploy ML models powering Snapchat features. You’ll apply ML techniques to solve real-world problems, participate in data analysis, training, and deployment, and work with cross-functional partners to ship scalable ML-driven capabilities. ...

agent ecosystems encompassing multi-agent orchestration, tool use, skills use, and memory systems, as well as foundation model integration, fine-tuning strategies, and classical ML model deployment within cohesive, production-ready platforms. You will be accountable for ensuring the complete architecture meets the most rigorous non-functional requirements across security … strategy — adaptation, fine-tuning, and dynamic cost/quality/latency-aware routing Set the standards for high-throughput, low-latency inferencing and classical ML deployment within unified, production-ready platforms Own the architecture of the enterprise context layer — knowledge graphs, ontologies, vector search, and semantic retrieval — grounding the solution ...