626 to 650 of 3,269 Machine Learning Jobs in the UK

Opportunity The Data Science team is growing at 9fin! We are doing world-class work with groundbreaking technologies to build data-driven products using machine learning, computer vision, natural language processing, speech and audio, and knowledge/data mining. We are looking for a Senior AI Engineer … Financial & Legal Domain Knowledge : Familiarity with leveraged finance, debt capital markets, credit agreements, covenant packages, bond documentation, restructuring processes, and related legal concepts. Production ML Engineering : Ability to build and operate extraction pipelines, evaluation systems, model-serving infrastructure, and monitoring for production AI workflows. Strong proficiency in Python for production ...

responsible data use Work collaboratively with Technical Engineers, Product Owners, and Solution Architects Requirements A minimum 3 years in data science, analytics, Agentic AI, machine learning or modelling is essential Proficiency in data analysis, customer analytics, building and validating models for forecasting, pricing, and segmentation and visualisation tools … e.g. Agentic AI, Machine Learning, Python, SQL, SAS, Power BI, Tableau) Experience with cloud-based data platforms (e.g. GCP native tools) Unafraid to challenge the status quo, have an intellectually curious outlook, where you seek to innovate and adapt quickly from setbacks. Apply product led thinking to reporting ...

Scientist to develop data science solutions that deliver measurable business impact across the organisation. Working within the Data team, you’ll use advanced analytics, machine learning and data engineering techniques to solve business problems, supporting projects from initial concept through to production deployment. You’ll collaborate closely with … translate them into scalable, data-driven solutions, while contributing to the continued development of our data science capability. Key responsibilities & opportunities Build and deploy machine learning models , taking solutions from initial ideation through to production deployment and ongoing optimisation. Design, develop and maintain scalable data models, ETL pipelines ...

Responsibilities Responsible for the technical development and leadership of AI/ML projects from initial idea scoping right through to final project delivery both in customer and internal domains. Demonstrate novel thinking and propose new ideas for solving challenging problems while mentoring others on your project team to deliver towards … solution. Develop complex, novel data science solutions, contributing significantly to machine learning projects with minimal guidance. Undertake research and applied AI/ML tasks on both customer and internal research projects. Generate ideas for new research directions and provide technical leadership in small project groups. Work with customers ...

architectures, agentic frameworks) for company-wide consumption. Product AI Integration: Collaborate directly with core engineering teams to embed production-ready generative AI and machine learning features into the Actian Data Intelligence Platform. LLMOps & Governance Infrastructure: Establish strict guardrails, evaluation frameworks, and monitoring tools to track model performance, bias … time-to-market for AI features, and ROI of implemented AI tools. Qualifications & Profile: Technical Background: Strong background as a Senior AI/ML Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms. AI & Engineering Mastery: Deep ...

both structured and unstructured formats. Using strong critical‐thinking and problem‐solving skills, you’ll analyse and interpret data, build predictive models, and develop machine learning algorithms that generate actionable insights. You’ll propose solutions to business challenges and collaborate with other teams to implement them. Recognising … Expertise: Strong analytical capability, with proven experience in statistical modelling skills, and data interpretation Technical Skills: Proficiency in Python for data analysis, modelling and machine learning. Machine Learning: Experience building and evaluating machine learning models Education: Degree in Mathematics, Statistics, Data Science, or another quantitative ...

capabilities beyond experimentation and into dependable products that operate safely and effectively at scale across our global marketplace. Working closely with software engineers, machine learning engineers, data scientists, product managers, analysts and technical leaders, you will shape how we build, test, deploy, monitor and govern AI‐powered systems. … reliability and security. Provide technical leadership to evolve AI solutions from experimentation into robust, observable and maintainable products. Collaborate cross‐functionally with product, engineering, ML and data teams to align technical decisions with user needs, business priorities and long‐term platform strategy. Define and drive engineering standards, reusable patterns, tools ...

generative AI gets built and operated responsibly at scale across the firm. You will Hire, structure, and develop a team of AI/ML and agentic software engineers. Set the bar for technical quality and the culture you want them to work in. Partner directly with business partners to understand … Protocol). Experience with MLOps/LLMOps tooling such as experiment tracking, model versioning, monitoring, evaluation/observability platforms, or CI/CD for ML and LLM systems. Experience implementing responsible‐AI or AI‐governance controls such as guardrails, human‐in‐the‐loop oversight, and audit trails in production. Experience ...

delivering technology that makes a real difference, this is the role for you. As a Senior Lead Software Engineer at JPMorganChase within the AI & ML Data Platforms team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products … maintainability Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile) Ability to tackle design and functionality problems independently with little to no oversight Practical cloud native experience with a strong understanding ...

into tailored solutions built on the SymphonyAI platform. You will need the technical depth to credibly engage with data science teams, configure and tune machine learning models against client data, and shape proposals that win competitive deals. Job Description What you will do Pre‐Sales engagement (around … prospect data, defining success criteria, managing risks, and working alongside the prospect's users to build the business case. Configure, tune and apply machine learning models — drawing on SymphonyAI's own algorithms and selected third‐party libraries — against client transaction, customer, and behavioural data to demonstrate detection performance. ...

with marketing, creative, and technical teams to understand their data needs and deliver tailored solutio ns.Innovate with Da ta: Use advanced statistical methods and machine learning algorithms to uncover trends, patterns, and opportunities that drive business grow th.Present Insigh ts: Communicate your findings to stakeholders in a clear … manner, making data relatable and actionab le.Mentor Junior Team Membe rs: Share your expertise and guide less experienced data scientists, fostering a culture of learning and collaborati on.What We’re Looking F or:Our client is seeking a talented individual with a blend of technical expertise and a flair ...

will play a key role in developing, implementing and monitoring these models and drive significant value for the business. Model Development: Develop statistical and machine learning models for commercial lending products. Optimization: Deliver value through the optimization of current models and drive innovation by constantly seeking alternative data … lift each other up and think smart every day. As part of the Decision Science team, you will create cutting edge statistical and machine learning models and collaborate with data engineers, analysts, and business stakeholders. As well as improving on our previous generation models, we are expanding ...

large data sets for anomalies or control gaps while maintaining data integrity across all surveillance and reporting systems. Support model validation processes including tuning machine learning models where applicable to enhance detection capabilities. Participate actively in change management activities such as system upgrades, patching cycles (SIT/… best practices. Experience working within Agile/Scrum delivery frameworks utilising JIRA/Confluence for project tracking/documentation purposes. Exposure to AI/ML frameworks such as TensorFlow or PyTorch along with practical experience deploying models into production environments; understanding model lifecycle management/monitoring processes. Previous involvement with ...

defined and ready for delivery. Establish measurable performance targets for analytics, tracking, classification and decision-support capabilities. Work closely with data scientists to translate machine learning and analytical models into production-ready features. Collaborate with software engineers, technical specialists and customers to refine requirements and validate delivered functionality. … radar, RF, electro-optical or other sensor technologies. Background in engineering, physics, mathematics, data science or a related technical discipline. Experience delivering AI, machine learning or analytics-driven products. Familiarity with decision-support systems or operational software platforms. Please note: This is a hybrid role based around regular ...

Tree-of-Thoughts, Reflexion , or hybrid reasoning patterns) for automation, insight generation, and decision support. Lead exploratory data analysis (EDA), dynamic source classification, and ML model integration for advanced analytical and operational use cases. Mentor and grow a high-performing team of architects, engineers, and analysts—fostering innovation, cross functional … reporting and observability Enterprise Integration: Secure API architecture, user feedback loops, instrumentation with Langfuse for traceability, MLOps and LLMOps frameworks to operationalise and govern ML/LLM pipelines across environments Your Profile Proven experience designing and scaling GenAI-enabled and data-driven architectures. Strong grounding in software engineering principles ...

learning frameworks (Pytorch, JAX, TensorFlow). You can work on different layers of the stack from low-level training backends, data ingestion to ML/RL algorithmic design and implementation. You know when and where to be rigorous and slower versus when to break and iterate quickly. You have … Publications in top-tier AI conferences (e.g., NeurIPS, ICML, CVPR, ACL, ICCV, AAMAS, ...) Advanced degree (PhD or MSc) in a relevant field (e.g., ML, DL, NLP, CV) Experience with large-scale distributed training and inference (multi-node, large models, MoE, parallelism strategies, etc) Experience training models for computer ...

your family again! Design reusable assets, solutions and develop best practices for current and future business problems. Consult on complex analyses and advanced machine learning methods. Communicate and provide guidance to senior client leadership and teams. Shape AI Strategy and the delivery of LLM based solutions. Operate across … production deployment. Consult on leveraging cloud platforms like AWS, Azure, and GCP to facilitate scalable model deployment. Partner with developers and engineers to deploy machine learning algorithms that drive measurable business value. Ensure Responsible and Ethical AI Collaborate with cloud vendors to integrate Responsible AI principles and standards ...

will help deliver scalable, secure, and reliable MLOps platforms supporting large-scale data processing and real-time inference workloads. Key Responsibilities Deploy and manage ML models in production using Azure Machine Learning. Design and maintain Azure-based MLOps infrastructure. Build and support Azure DevOps CI/CD pipelines … ML artefacts. Implement monitoring, logging, security, and governance controls. Manage data pipelines, storage solutions, data versioning, and lineage tracking. Support real-time inference and scalable ML workloads, including auto-scaling. Collaborate with technical and business stakeholders to optimise model performance and platform reliability. Produce and maintain technical documentation. Skills & Experience ...

Design, build and maintain scalable data pipelines and data platforms Develop analytics and AI-enabled solutions that support business decision-making Create and implement machine learning and generative AI solutions Integrate data from multiple sources while ensuring data quality and reliability Work closely with analysts, product teams … similar Strong programming skills in Python and SQL Experience building data pipelines and working with both structured and unstructured data Knowledge of AI, machine learning or generative AI technologies Exposure to frameworks such as TensorFlow, PyTorch, LangChain or similar Experience working with cloud based data platforms and modern ...

permanently in the Search Retrieval team. Within this role, you’ll be working in the cross-functional team in partnership with mobile, web and machine learning/data science teams to drive the team to success. Responsibilities: As a Backend Engineer within this team, you can expect … impacting product team and playing an integral role in improving how we help users find products they will love You have a passion for learning new things and growing your skills within a collaborative environment Familiarity with a high-level programming language (e.g. Python, Scala). You have ...

behaviour at scale, enabling Kantar’s products to test scenarios and predict outcomes before they happen. What you’ll be doing Developing and deploying machine‐learning models in production environments Working end‐to‐end across the data science lifecycle: problem definition, modelling, deployment and monitoring Analysing … data scientist on real‐world, production problems Strong Python skills (or a similar language used in applied data science) Experience with supervised learning and unsupervised techniques such as anomaly detection Exposure to cloud‐based model training, deployment and automation A strong sense of ownership and accountability for data science ...

design and validation of Agentic AI-driven product capabilities within Protégé in PatentSight. This role focuses on defining what to build and why, leveraging machine learning, NLP, and large language models (LLMs) to solve complex Intellectual Property (IP) workflows. You will help drive experimentation, modeling, and evaluation, partnering … align solutions with user needs. Requirements: Degree in a quantitative or technical field (Statistics, Computer Science, Mathematics, Data Science, etc.). Strong experience in machine learning, NLP, and LLM-based modeling. Strong experience designing and running experiments, including model evaluation and iteration. Strong coding skills in Python. Experience ...

genuine impact. This is a collaborative, hands-on environment where everyone contributes beyond traditional job boundaries. If you're someone who enjoys solving problems, learning new technologies and working directly with customers, you'll have the opportunity to make a real difference while shaping the future of AI adoption … translate them into practical AI solutions. Facilitating discovery workshops, technical discussions and solution design sessions with both technical and non-technical stakeholders. Developing machine learning models, AI applications and intelligent workflows that improve business processes. Designing scalable solution architectures and recommending the most appropriate technologies for each project. ...

lending decisions, enhance customer outcomes and support sustainable portfolio growth. Combining traditional data science techniques with practical commercial application, you’ll leverage modern analytics, machine learning and AI-assisted development tools to accelerate model development, improve decision making and deliver tangible business value. You’ll collaborate with stakeholders … Support the development of provisioning, forecasting and portfolio monitoring methodologies. Analyse customer, bureau, affordability and behavioural data to identify trends, risks and opportunities. Utilise machine learning and AI-assisted development techniques to accelerate model development and improve analytical efficiency. Produce robust model documentation, validation reports and governance materials. ...

Leveraged AI‐assistive development tools for tasks like scaffolding, refactoring, debugging, test generation, and documentation Experience building or integrating AI/ML‐powered features into products or systems (e.g., recommendation engines, NLP models, computer vision, predictive analytics) Used context‐appropriate automated testing to inform software design choices and catch bugs … balance technology choices while delivering high‐quality work within deadlines Leading architecture and software design discussions Collaborating on systems that involve the full ML lifecycle from data ingestion and preprocessing, to model deployment, integration, and performance monitoring Generating new potential solutions to challenges (technical and non‐technical) in partnership with ...