2,576 to 2,600 of 7,741 Machine Learning Jobs in the UK

knowledge of motor insurance pricing, burn cost modelling, rating structures, underwriting risk and claims cost drivers, with experience of statistical modelling, predictive analytics or machine learning techniques within a general insurance pricing environment. Pricing Technology & Data Platforms: Proficiency in pricing and data tools such as WTW Radar, Databricks … numerical capability, with strong attention to detail and the ability to challenge assumptions, methods and outputs. Experience using statistical modelling, predictive analytics or machine learning techniques within a general insurance pricing environment. Proficiency with pricing and data tools such as WTW Radar, Databricks, Python, PySpark, SQL or similar ...

internal processes Develop and deliver analytical solutions Design, build, and refine models and algorithms supporting experiments, prototypes, and minimum viable products, using statistical and machine learning approaches Translate ideas into structured solutions Turn business or innovation ideas into testable experiments to validate against the data or with … data science solutions, from exploration to deployment or handover Experience working with business stakeholders or product teamsTechnical skills Solid understanding of statistical methods and machine learning techniques, focused on timeseries data and text Strong programming skills in Python and experience with standard data science libraries such as pandas ...

hedge fund or investment bank Experience of web based development and visualisation technology for portraying large and complex data sets and relationships Experience of machine learning techniques, natural language processing and related libraries and frameworks e.g. scikit-learn, Tensorflow Personal Attributes Strong academic record and a degree with … have enormous impact on what we do. We are actively engaged with the broader technology community. We host and sponsor London’s PyData and Machine Learning Meetups We open-source some of our technology and tweet about relevant technology and how we’re using it. See @ManQuantTech ...

business recommendations Experience presenting insights and recommendations to stakeholders or clients Strong communication skills with the confidence to engage directly with customers Understanding of machine learning techniques and model development lifecycle Experience working with Databricks would be highly advantageous Exposure to cloud-based analytics environments, particularly Azure … collaboration across Data Science, Analytics, and Product teams Clear opportunities to develop both technical and client-facing skills A supportive environment that encourages continuous learning and professional growth How to Apply If you're a Data Scientist looking to work on impactful predictive modelling projects while developing your client ...

cutting edge of the field, with current research threads including:System Understanding: Interpretability, steering vectors, and the science of evaluations.Control & Alignment: Goal drift, machine unlearning, and uncertainty calibration.Societal Safeguards: Misinformation mitigation and robust deployment boundaries.We collaborate closely with the Faculty's wider AI safety team, a group with … academia, industry labs, or evaluation roles.Deep knowledge of language models and generative AI architectures, including white-box techniques beyond API-level access.Strong foundation in machine learning fundamentals, particularly in robustness, explainability, or uncertainty estimation.Proficiency with deep learning frameworks like PyTorch and the Python skills required to build ...

Model ML is the AI workflow builder transforming how major financial institutions produce and validate client-ready work. Model ML converts complex, manual processes into fully automated AI systems that scale across global teams. In under a year, Model ML has become one of the fastest growing enterprise AI platforms … timelines will change, priorities will most likely shift Be prepared to sacrifice your work-life balance in exchange for joining an incredible journey and learning a lot along the way. Requirements 5+ years of professional software engineering experience. Hands-on experience building and deploying AI applications in production environments. ...

Platform’s Core platform - the services and infrastructure that let us deploy to a multitude of public cloud providers and that powers many ML and LLM powered features. We give every other engineering team a reliable base to build on, and we own the software delivery lifecycle … This is an exciting opportunity to grow professionally while contributing to a mission-driven organization. Responsibilities What you’ll own Reliability of platform(includes ML and LLM workloads) - model serving and inference infrastructure (GPU-backed endpoints, autoscaling, latency and cost tradeoffs), with SLOs, on-call, and incident response that cover ...

ready global river data infrastructure.Reporting to Professor Louise Slater, you will lead research combining large-scale Earth observation data, global hydrography and advanced machine learning. The project will integrate measurements from the SWOT satellite mission with Oxford's Global River Topology (GRIT) hydrography to develop verified, uncertainty-aware predictions … river flow direction and connectivity.You will lead the development of scalable and reproducible data and machine-learning pipelines, upgrade the GRIT global hydrography, and design and evaluate models ranging from baseline approaches to graph neural networks. You will also oversee the open release of project datasets, models, code ...

systems such as Tanstack Query or Zustand. Strong proficiency with Python Familiarity with Git and software engineering principles Confidence in collaborating across disciplines, and learning new tools every day An appreciation for game design and development principles Nice to Have: Proficiency or familiarity with machine learning concepts ...

Data, Analytics and AI organisation of Arrive. The Data Science Products team ingests billions of complex sensor data points daily to produce advanced machine learning products that help millions of drivers park or charge electric vehicles. For example, we predict the availability of parking in cities across … services with high confidence and zero downtime. Advance Data Capabilities : Lead the hands-on development of platform enhancements, such as establishing feature stores for machine learning and building automated data monitoring systems to ensure data integrity and model reproducibility. Scale AI Practices : Lead the adoption of AI throughout ...

join a team where your work helps influence economies, your ideas can drive innovation and outcomes, and your growth is backed by mentorship, continuous learning and flexibility with potential hybrid work opportunities. Help solve real-world challenges that touch millions and get the opportunity to build the future … Hybrid: Demonstrated experience in a role that blends product management (defining the “what” and “why”) with software engineering (defining the “how”). AI/ML Expertise: Deep subject matter expertise in applying modern AI/ML techniques to solve real-world business problems. Experience with NLP, predictive modeling, or generative ...

Strong understanding of software engineering fundamentals, system design and performance optimisation. Experience building products and platforms from concept through to production. Exposure to AI, Machine Learning or LLM‐powered applications is highly desirable. A passion for modern engineering practices, continuous learning and solving complex technical problems. Benefits ...

join a team where your work helps influence economies, your ideas can drive innovation and outcomes, and your growth is backed by mentorship, continuous learning and flexibility with potential hybrid work opportunities. Help solve real-world challenges that touch millions and get the opportunity to build the future … Engineering Hybrid: Demonstrated experience in a role that blends product management (defining the "what" and "why") with software engineering (defining the "how").AI/ML Expertise: Deep subject matter expertise in applying modern AI/ML techniques to solve real-world business problems. Experience with NLP, predictive modeling, or generative ...

Model ML is the AI workflow builder transforming how major financial institutions produce and validate client-ready work. Model ML converts complex, manual processes into fully automated AI systems that scale across global teams. In under a year, Model ML has become one of the fastest growing enterprise AI platforms … uncomfortable; timelines will change, priorities will most likely shift Be prepared to sacrifice your work-life balance in exchange for joining anincredible journey and learning a lot along the way. Requirements Technical Technical stack : Azure (also AWS is a plus), Terraform, AKS (Kubernetes), Docker, Github actions. Observability: Experience implementing ...

role with a strong Machine Learning and Large Language Model (LLM) focus, ideal for a Python Engineer who has experience working with ML/LLM technologies. You will work alongside Software Engineers, Machine Learning specialists and the wider technology team to deploy, integrate and optimise innovative … with Machine Learning and Large Language Models (LLMs) this is an essential requirement for the role Experience deploying, integrating or working with ML/LLM models in practical applications Familiarity with machine learning frameworks, model deployment and inference technologies Experience using Python data and matrix manipulation ...

fleet (VS Code, Python, Git, CLI utilities), balancing developer flexibility with security and compliance standards. Define and support endpoint requirements for AI/ML workloads, including GPU driver management, containerization/WSL2, and local model runtime resource sizing. Partner with engineering and data teams to evaluate, standardize, and roll … Support, Including Configuring and troubleshooting VS Code, Python, and common CLI/developer environments Git‐based version control workflows Endpoint requirements for AI/ML workloads (GPU drivers, WSL2/containers, local model runtimes, resource sizing) Applying governance and device‐management guardrails to developer and AI tooling without blocking productivity ...

evidence-generation approaches. Shape long-term evidence strategies for priority assets and disease areas while identifying opportunities to leverage new data sources, advanced analytics, machine learning, and artificial intelligence. Serve as a trusted scientific advisor, championing robust methodologies and evidence-based decision-making across the organization.Interested? For this … innovative real-world evidence study designs, external control arms, comparative effectiveness research, and post-authorization safety or effectiveness studies. Interest in applying advanced analytics, machine learning, and artificial intelligence to real-world data and evidence-generation activities. Demonstrated ability to influence stakeholders and translate complex evidence into actionable ...

Platform Engineer London Company Overview Model ML is the AI workflow builder transforming how major financial institutions produce and validate client‐ready work. Model ML converts complex, manual processes into fully automated AI systems that scale across global teams. In under a year, Model ML has become … timelines will change, priorities will most likely shift. Be prepared to sacrifice your work‐life balance in exchange for joining an incredible journey and learning a lot along the way. Requirements Technical stack : Azure (also AWS is a plus), Terraform, AKS (Kubernetes), Docker, GitHub Actions. Observability : Experience implementing logging ...

looking for a Lead AI Engineer (Senior/Principal Consultant) to join our Technology Delivery Team. You’ll combine your expertise in AI/ML engineering and software development to build and deploy cutting-edge generative AI and agentic systems across the financial services sector. As a hands-on leader … native AI deploymentExcellent communication, problem-solving, and project management skills in agile environmentsBonus Points ForExperience with agentic frameworks (e.g., LangChain, LlamaIndex)Experience in deep learning frameworks and front-end developmentFamiliarity with Langfuse, Langsmith, or other LLM observability toolsUnderstanding of Model Context Protocol and bias/hallucination mitigation techniquesPrevious success ...

across the fleet (VS Code, Python, Git, CLI utilities), balancing developer flexibility with security and compliance standards.Define and support endpoint requirements for AI/ML workloads, including GPU driver management, containerization/WSL2, and local model runtime resource sizing.Partner with engineering and data teams to evaluate, standardize, and roll … workload support, including:Configuring and troubleshooting VS Code, Python, and common CLI/developer environmentsGit-based version control workflowsEndpoint requirements for AI/ML workloads (GPU drivers, WSL2/containers, local model runtimes, resource sizing)Applying governance and device-management guardrails to developer and AI tooling without blocking productivityAbility ...

experienced multi-disciplinary team developing and maintaining data science, AI and simulation models, designed to solve client problems.Responsibilities include:Apply data science, machine learning, and AI techniques to extract insights and deliver business value from structured and unstructured data.Develop and maintain data science, AI or Simulation models written … critical thinking skills, with a creative approach to tackling challenges.Proven foundation in statistics, probability, and data analysis techniques.Significant hands-on experience in data science, machine Learning, and AI, with a track record of delivering solutions in a professional setting.Hands-on experience with LLMs, including RAG, fine-tuning ...

fleet (VS Code, Python, Git, CLI utilities), balancing developer flexibility with security and compliance standards. Define and support endpoint requirements for AI/ML workloads, including GPU driver management, containerization/WSL2, and local model runtime resource sizing. Partner with engineering and data teams to evaluate, standardize, and roll … support, including: Configuring and troubleshooting VS Code, Python, and common CLI/developer environments Git-based version control workflows Endpoint requirements for AI/ML workloads (GPU drivers, WSL2/containers, local model runtimes, resource sizing) Applying governance and device-management guardrails to developer and AI tooling without blocking productivity ...

problem-solving skills. Ability to influence technical direction and work autonomously. Desirable Cybersecurity, malware analysis, threat detection, or security product experience. Statistical analysis, machine learning, or complex systems experience.Previous mentoring or technical leadership experience. Work on genuinely challenging technical problems, shape innovative products, and collaborate with some ...

journeys. You will be responsible for defining strategy, prioritising investments, and delivering measurable outcomes across document verification capabilities, working closely with Engineering, AI/ML, Product Design, Operations, and Growth teams. This is an excellent opportunity for someone who wants to help shape the future of digital identity, as identity … Document Verification portfolio. Analyse customer journeys and product performance to identify opportunities to improve verification outcomes. Partner closely with Engineering, AI/ML, Data Science and Design to deliver innovative document verification capabilities. Drive improvements in verification accuracy, customer conversion, operational efficiency and fraud prevention. Work closely with Growth, Customer ...

Testing: Design, execute, and analyze rigorous A/B and multivariate tests to measure feature performance, user retention, and business impact. Predictive Analytics & Machine Learning: Build, validate, and maintain scalable predictive models (e.g., churn, forecasting, customer lifetime value (CLV) and user segmentation) to guide business decisions. Exploratory Data … writing optimized, complex queries across large cloud data warehouses (e.g., Snowflake, BigQuery). Programming & Modelling: Strong proficiency in Python for statistical modeling, forecasting, and machine learning. Statistics & Math: Deep understanding of statistical inference, regression analysis, probability theory, decision trees, and hypothesis testing (p-values, confidence intervals, Bayesian testing etc. ...