151 to 175 of 439 Machine Learning Jobs in London

/CV to me, Dan - WHO WE ARE: We're an EdTech startup using AI and data-driven technology to transform how students learn and educators teach. Our intelligent learning platform empowers users through personalised insights, automating complex processes and enabling smarter decision-making. As we continue to scale, we're strengthening our technical delivery capability and looking for … TO HAVE: Certifications such as PMI-ACP , PMP , or Agile Practitioner . Experience working in cloud environments (GCP, AWS, or Azure). Previous exposure to data engineering, AI , or machine-learning teams . Familiarity with data and analytics technologies (ETL tools, data warehouses, dashboards). TO BE CONSIDERED... Please either apply online or email me directly at .By More ❯

to build consensus with stakeholders, both internally and externally Possess deep knowledge of modern cloud infrastructure, including Infrastructure as Code, AWS, and GCP Strong candidates may have: Experience with machine learning infrastructure like GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL Low-level systems experience, for example Linux kernel tuning and eBPF Experience building … many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation More ❯

Snowflake, Databricks, Spark) and ETL processes. Useful experience; Python or R for advanced analytics, automation, or experimentation support. Knowledge of statistical methods and experimentation (A/B testing) preferred. Machine learning and Generative AI experience is a plus. Experience working with call centre and/or sales operations. Benefits Long contract Hybrid role Free breakfast More ❯

adaptable, and comfortable in a smaller, fast-moving team environment Excellent communication skills and ability to take ownership of projects Experience delivering actionable insights rather than exploratory or purely machine learning work Interview Process: Remote competency interview and CV review Face-to-face interview with testing component (details to be confirmed) Find out more and apply via the More ❯

on Data & Analytics) or equivalent in a global enterprise. Recognised thought leader in Data and Analytics (e.g., DataIQ Top 100, industry awards, keynote speaker). Expertise in AI strategy, machine learning, and enterprise data platforms. Strong understanding of cloud technologies (AWS, Azure, GCP) and modern data architectures. Exceptional stakeholder management and communication skills. Certifications such as CDAO, AI More ❯

to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm's commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly. Job Responsibilities Partners with CDO office to drive adoption and roll-out of More ❯

Background in data management, engineering, or database administration . Experience with metadata management and master data management (MDM) tools. Understanding of data governance frameworks and compliance standards. Familiarity with machine learning pipelines or AI model integration. A proactive, detail-oriented approach and a passion for building scalable, reliable data systems . TO BE CONSIDERED... Please either apply online More ❯

pipeline logic and contribute to business-wide metadata catalogues Collaborate with BI, Change, and Product teams to align data outputs to needs Support groundwork for future data science and machine learning initiatives The successful applicant will be proficient in SQL and Python, with a proven track record of building and maintaining ETL/ELT pipelines. Experience working with More ❯

footballers' legs. Ki's mission is 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. It is the fastest More ❯

and Know Your Customer (KYC) provider. We were founded to solve the specific challenges faced by companies trying to onboard users in unique African conditions. We have built proprietary machine learning algorithms and a technology platform to cater for all skin tones, entry level devices and users operating in low bandwidth environments. We pride ourselves on striking the More ❯

record of working with traders or other business stakeholders to create commercially actionable models. Experience with a range of modelling techniques including, regression, time series analysis, forecast modelling and machine learning. Excellent problem-solving skills. Experience using a coding language to develop models and analytical tools. Experience manipulating and analyzing large, complex datasets. Desirable Experience & Skills Practical knowledge of More ❯

Experience Proven experience leading technical delivery of AI/automation solutions using Microsoft Copilot Studio and Power Platform. Hands-on expertise in Python for automation, integration, or AI/ML tasks. Strong understanding of MCP (Microsoft Cloud Platform), A2A (Application-to-Application) integration, and Azure AI Foundry. Track record of embedding controls, governance, and compliance in technical solutions. Experience in More ❯

or F&B industries is highly desirable Nice to Have Experience in SaaS or AI-driven product environments (highly valued) Experience building or managing data platforms, analytics products, or ML/AI features Experience managing products during company transitions or rapid scaling Familiarity with UI/UX, ETL processes, data pipelines, and data validation workflows What's on Offer? Excellent More ❯

etc Management and leadership of multi-disciplinary teams within data – Data Science, Data Analysis, Engineering/ETL, Data Visualisation Experience of developing and, critically, delivering AI/NLP/ML and predictive analytics capability within commercial environments. Experience of ensuring that all data-related activities comply with regulatory industry standards An ability to influence across all departments at the most More ❯

an application demo portal, showcasing the latest and greatest in cloud and application architecture Lead on AI driven approaches to application development and management, helping our customers embed AI, ML and automation into process flows Collaborate with sales, pre-sales and cloud teams across the full customer lifecycle to be an expert on engineering modern applications Work with our tooling More ❯

Strong consulting skills, including targeted communication, engagement management, stakeholder management, and business development. Mastery of enterprise architecture components, business/IT principles, and organisational processes. Experience applying AI/ML across corporate functions (e.g., financial anomaly detection, HR attrition prediction, procurement spend analytics). Competencies Exceptional analytical, planning, and organisational capabilities, with strong situational awareness and political acumen. Balances long More ❯

early in the lifecycle. Continuous Improvement Identify opportunities to simplify and modernise the data landscape by rationalising legacy platforms and redundant data stores. Stay current with emerging technologies (AI, ML, data mesh, data fabric) and translate them into tangible business capabilities. Contribute to the refinement of the North Star architecture and enterprise data capability roadmap. Key Interfaces Enterprise Architecture Domains More ❯

early in the lifecycle. Continuous Improvement Identify opportunities to simplify and modernise the data landscape by rationalising legacy platforms and redundant data stores. Stay current with emerging technologies (AI, ML, data mesh, data fabric) and translate them into tangible business capabilities. Contribute to the refinement of the North Star architecture and enterprise data capability roadmap. Key Interfaces Enterprise Architecture Domains More ❯

as Jenkins, ADO, GitHub actions, CirlceCI etc. Awareness of the latest developments in testing tools and design patterns. Bonus Points for: Experience with emerging technologies, e.g using AI/ML within your engineering projects. Familiarity with testing in cloud environments such as AWS, Azure or Google Cloud . Whats in It for You? We believe in rewarding great work. Heres More ❯

to high value work that transforms customer experience. Our goal is to drive innovation and guide our clients' digital supply chain transformation journeys, leveraging innovative technology i.e., AI/ML, predictive and prescriptive analytics to enable decision automation and increased operational efficiency. We are a global team and operating from various locations in Europe, North America, and India. We focus More ❯

to high value work that transforms customer experience. Our goal is to drive innovation and guide our clients' digital supply chain transformation journeys, leveraging innovative technology i.e., AI/ML, predictive and prescriptive analytics to enable decision automation and increased operational efficiency. We are a global team and operating from various locations in Europe, North America, and India. We focus More ❯

and privileged access policies with data security controls. Deliver security capabilities that support modern work scenarios, remote access, zero-trust networking, and protection of sensitive data in AI/ML workloads. Leverage automation frameworks and IaC to improve scalability and reduce manual intervention. Operational Security, SRE & Assurance: Ensure security platforms are resilient, continuously monitored, and designed for 24x7 support and More ❯

of high-end GPUs. We don't believe in "one-size-fits-all" modelling solutions; we are open to and excited about applying all different types of statistical and ML techniques, from linear models to deep learning, depending on what best fits a given problem. You'll spend the bulk of your internship working closely with full-time researchers … on projects drawn from their own work. You'll gain a better understanding of the diverse array of challenges we consider every day, learning how we think about experiment design, dataset generation, time series analysis, feature engineering, and model building for financial datasets. Your day-to-day project work will be complemented by classes on the broader fundamentals of … a career in finance, you're in good company. Many of us were in the same position before working here. Most candidates will have experience with data science or machine learning, but ultimately, we're more interested in how you think and learn, than what you currently know. You should be: Able to apply logical and mathematical thinking More ❯

and implement data pipelines for model-ready datasets in collaboration with data engineering teams. Apply feature engineering and selection techniques to improve model accuracy and interpretability. Develop and validate machine learning and statistical models for prediction, classification, clustering, or optimization. Apply supervised and unsupervised learning techniques using libraries such as Scikit-learn, TensorFlow, or PyTorch. Implement NLP More ❯

frameworks (e.g. LangChain, CrewAI, AutoGen) Promote responsible and ethical AI standards across solutions What You'll Bring Strong background in software/platform/DevOps architecture with AI/ML exposure Experience in using Azure Open AI and/or AWS Bedrock Hands-on experience deploying agentic or autonomous AI systems in production. Proficiency in Python Excellent communicator with consulting … or client-facing experience Knowledge of AI governance, interpretability, and bias mitigation principles Desirable Familiarity with IaC (Terraform, Bicep) Previous exposure to Machine Learning, Data Science or MLOps System Design More ❯