826 to 850 of 4,290 Machine Learning Jobs in the UK

to influence actual changes in government policies through innovation. JOB DESCRIPTION: As a newly created role for a team of four, you will integrate large-scale data preprocessing with machine learning, transparent integration, and the use of data structures and algorithms, enabling training models leveraging a distributed in-memory machine learning platform. Areas to cover will … operate a full-stack system. Areas to improve will include replacing existing workflows with advanced machine learning algorithms, including NLP and ensemble methods using powerful data munging, ML pipelines with advanced algorithms fully deployed for speed and accuracy with graphical user interface (GUI). You will also participate in software development meetings with the CEO, CTO, CIO, V.P … into a tokenizer. Proficiently fitting implementing methods that accept data-frames and produce models into transformers. In-depth knowledge of deployment of chains, multiple transformers, and estimators to create ML workflow. Develop detailed analyses repeatedly evaluating different features in engineering steps, algorithms, hyper-parameters, train original datasets, and cross-validation. Superior ability to build and execute specifying a list of More ❯

our dynamic Innovation Group. In this role, you will direct AI-driven solutions, apply plasma physics expertise, and guide a multidisciplinary team using Python. Candidates with advanced AI/ML expertise or a physics background-particularly in plasma science-coupled with professional AI/ML experience are encouraged to apply. This position offers a unique opportunity to advance semiconductor technologies … plasma physics insights to innovate semiconductor solutions, such as plasma etch and deposition. Utilize Python libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) to architect and prototype cutting-edge ML systems, leveraging Linux environments. Able to expand programming expertise to other languages such as C++ and Java. Drive complex AI and physics-driven projects, collaborating with engineering, application, and customer … support teams to deliver market-ready products. Mentor and coach team members, fostering expertise in AI, ML, and physics within the Innovation Group, and assume leadership roles as required. Shape our AI-powered product roadmap, identifying new opportunities by adapting technologies from diverse fields. Build strong customer partnerships, communicating technical benefits and supporting global projects, with occasional international travel. What More ❯

lead a team of solution architects, and drive best practices in data governance, security, and advanced analytics. You will work closely with business leaders, data engineers, and AI/ML teams to build a modern, future-proof data ecosystem that supports data-driven innovation. The ideal candidate must have: Experience in data architecture, solution architecture, or cloud data engineering, with … mentoring teams in data platform architecture and solution design. Extensive experience with data integration, MDM, data governance, and data quality tools. Experience designing and integrating Machine Learning (ML) architectures on Azure, including: MLOps and model lifecycle management in Azure ML and Databricks. Model deployment, serving, and monitoring within a Lakehouse or Data Mesh framework. Proficiency in Apache Spark More ❯

Job ID: Amazon Development Centre (Scotland) Limited We're looking for a Machine Learning Scientist in the Personalization team for our Edinburgh office experienced in generative AI and large models. You will be responsible for developing and disseminating customer-facing personalized recommendation models. This is a hands-on role with global impact working with a team of world … class engineers and scientists across the Edinburgh offices and wider organization. You will lead the design of machine learning models that scale to very large quantities of data, and serve high-scale low-latency recommendations to all customers worldwide. You will embody scientific rigor, designing and executing experiments to demonstrate the technical efficacy and business value of your … which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment. BASIC QUALIFICATIONS - PhD, or a Master's degree and experience in CS, CE, ML or related field - Experience in patents or publications at top-tier peer-reviewed conferences or journals - Experience programming in Java, C++, Python or related language - Experience in any of the More ❯

of our Supply Chain from our suppliers to our customers. We are also responsible for analyzing the performance of our Supply Chain end-to-end and deploying Operations Research, Machine Learning, Statistics and Econometrics models to improve decision making within our organization, including forecasting, planning and executing our network. We work closely with other Supply Chain Optimization Technology … and clearly communicate results and recommendations to leadership - Act as an active member of the science community by researching, applying and publishing internally/externally the latest OR/ML techniques from both academia and industry BASIC QUALIFICATIONS - PhD, or a Master's degree and 5+ experience applying theoretical models in an applied environment - Experience in solving business problems through … years experience in developing OR algorithm for non-convex and non-linear optimization problems - 2+ years experience with Stochastic Optimization algorithms (e.g. Stochastic Linear Programming, Stochastic Dynamic Programming) and ML for Probabilistic Forecasting - Sharp analytical abilities, excellent written and verbal communication skills - Ability to handle ambiguity and fast-paced environment PREFERRED QUALIFICATIONS - Experience in professional software development - Reinforcement Learning More ❯

will be joining an organisation where data drives strategic decision-making within the property space. You’ll lead the data science vision while remaining hands-on with AI and machine learning initiatives that have real business impact. This is ideal for someone who enjoys blending leadership, strategy, and technical depth. This would be a great opportunity for someone … their career - I.e. Someone at the Principal, Manager, Head of Data Science level. Key Responsibilities Define and deliver the data science strategy to unlock business value. Identify AI/ML opportunities and develop impactful, scalable solutions. Lead and mentor a cross-functional team of scientists and engineers. Stay hands-on where needed, guiding model design, code reviews, and architecture decisions. … We’re Looking For MSc/PhD in Data Science, Computer Science, Maths or similar. Hands on experience in data science or AI, including leadership roles. Deep expertise in machine learning, NLP, and predictive modelling. Proficient in Python or R, cloud platforms (AWS, GCP, Azure), and big data tools (e.g. Spark). Strong business acumen, communication skills, and More ❯

will be joining an organisation where data drives strategic decision-making within the property space. You’ll lead the data science vision while remaining hands-on with AI and machine learning initiatives that have real business impact. This is ideal for someone who enjoys blending leadership, strategy, and technical depth. This would be a great opportunity for someone … their career - I.e. Someone at the Principal, Manager, Head of Data Science level. Key Responsibilities Define and deliver the data science strategy to unlock business value. Identify AI/ML opportunities and develop impactful, scalable solutions. Lead and mentor a cross-functional team of scientists and engineers. Stay hands-on where needed, guiding model design, code reviews, and architecture decisions. … We’re Looking For MSc/PhD in Data Science, Computer Science, Maths or similar. Hands on experience in data science or AI, including leadership roles. Deep expertise in machine learning, NLP, and predictive modelling. Proficient in Python or R, cloud platforms (AWS, GCP, Azure), and big data tools (e.g. Spark). Strong business acumen, communication skills, and More ❯

solutions meet business and user needs. In addition to a focus on observability, you will contribute hands-on by developing features, automating workflows, and supporting the deployment of advanced machine-learning models. Strong communication skills are vital for working effectively with engineers, product teams, and stakeholders across the organization. About AudioStack AudioStack is the world's most powerful … automating these processes. You'll also take a key role in developing our product and customer analytics at AudioStack. You will be working as part of our AI/ML team, working closely with our machine learning engineers, software engineers, and product owners to ensure we are best in the industry. What you'll be doing: Responding to … platform Investigating performance issues and runtime errors Writing and shipping features for our customers - we expect everyone to be engineers as well! Accelerating our CI/CD process Deploying Machine Learning models onto GPU-based systems on AWS Supporting engineers on high-value deployments and teaching best practices about CI/CD to these engineers Identifying and resolving More ❯

delivering 10x improvements by supporting them in their day-to-day tasks. Responsibilities: Contributing by processing, analyzing, and synthesizing information applied to a live client problem at scale. Developing machine learning models to extract insights from both structured and unstructured data in areas such as NLP and Computer Vision. The role requires skills in both prototyping and developing … Learning, Deep Learning, NLP and Computer Vision. Experience with Large Scale/Big Data technology, such as Hadoop, Spark, Hive, Impala, PrestoDb. Hands-on capability developing ML models using open-source frameworks in Python and R and applying them on real client use cases. Proficient in one of the deep learning stacks such as PyTorch or More ❯

party publishers; and extends across US, EU and an increasing number of international geographies. We are looking for a dynamic, innovative, and accomplished Senior Applied Scientist to work on machine learning initiatives that power our brand safety solutions. The role requires developing and fine-tuning Large Language Models at scale, designing content filtering systems, implementing alignment techniques, and … and classification, traffic quality prediction (robot and fraud detection), Security forensics and research, Viewability prediction, Brand Safety and experimentation. Our team includes experts in the areas of distributed computing, machine learning, statistics, optimization, text mining, information theory and big data systems. BASIC QUALIFICATIONS - Experience programming in Java, C++, Python or related language … Experience with neural deep learning methods and machine learning - Experience in building machine learning models for business application - Experience in applied research - PhD in ML and 5+ year of industry experience PREFERRED QUALIFICATIONS - Demonstrated expertise in scaling Large Language Models (LLMs) for production environments, including optimization techniques for inference and training Amazon is an equal More ❯

About the role Join our Optimization team at Taktile as a Full-Stack Engineer. You will build isolated, scalable data warehouses for finance data on AWS. Develop operational, ML/AI and visualizations tools to help customers derive value from their data. Your contributions will directly enhance our automated decisioning platform, allowing users to improve financial decision policies at scale … What You'll Do Build customer facing data interfaces with React to manage and communicate decision policy performance Develop data-backed tools for improving policy performance, such as training ML models on historical data and backtesting at scale. Design and develop scalable RESTful APIs using Python on AWS, leveraging services such as Lambda, S3 and SQL. Optimize data warehouse efficiency … Taktile is based in Berlin, London and New York City. It was founded by machine learning and data science veterans with extensive experience building and running production ML in financial services. Our team consists of engineers, entrepreneurs, and researchers with a diverse set of backgrounds. Some of us attended top universities such as Harvard, Oxford, and Stanford and More ❯

BigQuery and PostgreSQL) proficiency and Python programming skills Experience with Google Cloud Platform Experience with big data warehouse systems (Google BigQuery, Apache Hive, etc) Hands on experience working with machine learning teams; understanding of the core concepts of model evaluation techniques and metrics, and suitable choices of their usage Experience working with data visualisation tools, particularly … Grafana Strong communication skills for client-facing interactions Collaborative mindset for cross-functional work Nice to Have Experience with image based machine learning Experience with AI/ML deployment workflows Experience communicating with non-technical stakeholders (client and internal) Startup experience This position offers significant growth potential in a fast-paced environment where you'll work with cutting More ❯

BigQuery and PostgreSQL) proficiency and Python programming skills Experience with Google Cloud Platform Experience with big data warehouse systems (Google BigQuery, Apache Hive, etc) Hands on experience working with machine learning teams; understanding of the core concepts of model evaluation techniques and metrics, and suitable choices of their usage Experience working with data visualisation tools, particularly … Grafana Strong communication skills for client-facing interactions Collaborative mindset for cross-functional work Nice to Have Experience with image based machine learning Experience with AI/ML deployment workflows Experience communicating with non-technical stakeholders (client and internal) Startup experience This position offers significant growth potential in a fast-paced environment where you'll work with cutting More ❯

skills coverage across the below items. If you consider yourself an expert in 1 or more of these skills then we would love to work with you! AI/ML Solution Architecture: Designing and deploying machine learning models and AI solutions tailored to engineering and data team workflows. Agentic AI Design: Expertise in building autonomous AI agents capable … data pipelines, ETL automation, and leveraging AI for data quality and governance. AI Infrastructure & MLOps: Experience with cloud AI services, model deployment, monitoring, and CI/CD pipelines for ML models (MLOps best practices). Example Tools & Technologies: Frameworks & Libraries: LangChain, Hugging Face Transformers, PyTorch, TensorFlow, Scikit-learn Agentic AI Tools: OpenAI GPT models, Crew,AI, Cohere, Pinecone (for vector … databases), AutoGPT Data Engineering & ML Pipelines: Apache Airflow, MLflow, Kubeflow, dbt, Prefect Cloud & Deployment Platforms: AWS SageMaker, Azure ML, Google Vertex AI APIs & Orchestration: OpenAI API, Anthropic Claude, Weaviate, FastAPI (for AI applications) MLOps & Experimentation: Weights & Biases, DVC (Data Version Control), Docker, Kubernetes General 2+ years of professional experience in relevant fields. Experience mentoring, coaching, or teaching others in a More ❯

data-driven strategies. Data Management: Identify, collect, clean, and process relevant datasets, ensuring seamless handover to Data Engineers. Model Development: Create and deploy predictive and prescriptive models using Azure ML Studio and Azure DevOps. Effective Communication: Present findings clearly through visualisation and reporting, including interactive dashboards and web applications using Power BI, R Shiny, or Python Flask. MLOps Maintenance: Maintain … a candidate with a blend of essential skills and experience, including: Hands-On Experience: Proven experience in data science and machine learning model deployment, preferably with Azure ML Studio. MLOps Proficiency: Strong understanding of pipeline management and model versioning. Data Manipulation Skills: Expertise in data extraction, transformation, and reshaping using SQL, R/Tidyverse, and Python/Pandas. … BI, R Shiny, and Python Flask. Agile Methodology: Familiarity with Git and Azure DevOps for version control and agile task management. Statistical Acumen: Solid understanding of statistical methods and machine learning algorithms. Effective Communication: Ability to convey complex technical concepts to both technical and non-technical audiences. Problem-Solving Attitude: Strong proactive approach to identifying and resolving challenges. More ❯

relevance and related experiences for customers. BASIC QUALIFICATIONS - PhD, or Master's degree and 5+ years of applied science experience - Skilled in Python or alternative programming language. - Experience in ML model productionization. - Ability to manage and quantify improvement in customer experience or value for the business resulting from research outcomes - Superior verbal and written communication skills, ability to convey rigorous … mathematical concepts and considerations to non-experts. PREFERRED QUALIFICATIONS - A PhD in a quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent) and 5+ years of experience working in data science in a consumer product company - Practical experience in several of the following areas: machine learning, statistics, NLP, deep learning, recommendation systems, computer More ❯

and consultancy are looking for an AI Engineer/Consultant to join their expanding AI specialist team. The chosen candidate will have experience in AI (specifically Gen AI) and ML, coupled with Azure exposure. Salary & Benefits Competitive salary of up to £60k Performance-related bonus of 10% Fully remote working Flexible working hours 25 days annual leave Monthly home working … with clients to identify business challenges and opportunities for AI solutions. Design and develop AI models and algorithms to address client needs. Provide technical expertise in AI technologies, including machine learning, natural language processing, and computer vision. Demonstrate understanding of navigating AI best practices within an Azure Data Engineering environment. Conduct data analysis and preprocessing to prepare datasets … make necessary adjustments. Provide training and support to clients on AI tools and best practices. What do I need to apply for the role Proven experience in AI and machine learning, with a proven track record of successful projects. Proficiency in programming languages - Python essential. Experience with AI frameworks and libraries. Excellent communication and interpersonal skills. Experience with More ❯

monitoring, and maintenance of machine learning models in production. Acting as the critical link between the data science and R&D teams, this team will ensure that ML models transition smoothly from development to production, maintaining high availability, scalability, and performance. Key responsibilities include: Managing and optimising existing ML model deployments to ensure reliability and efficiency. Continuously improving … for model deployment, monitoring, and lifecycle management. Collaborating closely with data scientists to understand and implement model requirements. Partnering with R&D teams to align technical strategies and integrate ML solutions into broader systems. Implementing robust CI/CD pipelines, monitoring systems, and infrastructure automation. Upholding best practices in security, cost management, and infrastructure design for cloud environments. This team … will play a pivotal role in ensuring that ML initiatives drive value effectively while maintaining operational excellence and we're looking for a Senior Software Engineer to be part of it! Responsibilities : Architect and develop robust pipelines for ML model training, testing, and deployment. Implement and maintain CI/CD workflows for ML projects. Monitor production ML systems for performance More ❯

for leading GSI in the software engineering market AI Solution Architect to design and implement AI-driven agent solutions for the online commerce space. Deep understanding of AI/ML models, cloud computing, and scalable system architecture. This role requires expertise in architecting intelligent agents, optimizing cloud-based deployments, and integrating AI services into enterprise applications. Key Responsibilities: Architect and … ECS, etc.) to deploy scalable AI solutions. Implement Full Stack JavaScript (Node.js, React.js, Express, TypeScript, Next.js, etc.) applications to support AI-driven interfaces. Work closely with data scientists and ML engineers to integrate machine learning models into cloud-native applications. Ensure security, scalability, and reliability of AI agent solutions in production environments. Design event-driven and serverless architectures … governance. Required: 5+ years of experience in solution architecture with a focus on AI, APIs, and cloud technologies. Strong hands-on experience with AWS services related to AI/ML and serverless computing. Proficiency in JavaScript, TypeScript, Node.js, React.js, and Express.js for building full-stack applications. Experience with AI/ML frameworks such as TensorFlow, PyTorch, OpenAI API, or LangChain. More ❯

ability to bridge the gap between business needs and AI solutions. Responsibilities: Design, develop, and implement AI solutions using Microsoft AI technologies such as Azure OpenAI, LLMs & SLMs, Azure Machine Learning, Cognitive Services, and Azure AI Document Intelligence, with additional experience in Fabric, PowerBI, DataBricks, and LangChain. Work closely with clients to understand their architecture and integration needs … candidate: 5+ years of experience in AI, Machine Learning, GenAI, or Data Science, with expertise in Microsoft AI technologies. Hands-on experience with Azure OpenAI, LLMs, Azure ML, Cognitive Services, Synapse, Fabric, and Power Platform AI capabilities. Strong programming skills in Python, C#, or other relevant languages for AI model development. Experience deploying AI solutions in enterprise environments More ❯

you'll help build a fairer credit system. The Role We're looking for an experienced MLOps Engineer for a 3-month contract to lead the development of our ML deployment, testing, monitoring, and feature engineering pipelines . You'll be responsible for establishing best practices and production-grade systems to support our machine learning workflows from training … ensure stability and quality. - Establish model monitoring and alerting frameworks for real-time and batch inference (e.g., model drift detection, performance degradation). - Build CI/CD pipelines for ML workflows (training, evaluation, deployment), integrating with tools such as GitHub Actions , CodePipeline , or Jenkins . - Create internal documentation and onboarding guides for engineering and data teams to adopt new MLOps … practices. What We're Looking For - 3+ years of experience in MLOps, DevOps, or ML infrastructure roles. - Deep familiarity with AWS services , especially SageMaker , S3, Lambda, CloudWatch, IAM, and optionally Glue or Athena. - Strong experience with MLflow , experiment tracking , and model versioning. - Proven experience setting up and managing a feature store , and driving best practices for feature engineering in production More ❯

millions of data points per second from LSE, Bloomberg, and alternative data sources Autonomous AI Agents: Build intelligent agents for trading, compliance, research, and risk management Predictive Analytics: Develop ML models for earnings prediction, M&A identification, and market regime detection Technical Infrastructure Cloud-Native Architecture: Multi-region deployment (London/Dublin/Frankfurt) with auto-scaling Real-time Data … Integrations: Bloomberg Terminal, Refinitiv, prime brokerage APIs, and regulatory systems Advanced Security: Zero-trust architecture, FCA compliance, and financial-grade security protocols 🔧 Technical Stack You'll Lead AI/ML: TensorFlow, PyTorch, MLflow, NVIDIA Triton, custom financial LLMs Data: Kafka, Flink, Snowflake, ClickHouse, Neo4j, vector databases Backend: FastAPI, GraphQL, microservices, Docker, Kubernetes Frontend: React/Next.js, TypeScript, real-time dashboards … discriminate on age and experience Proven track record building and scaling B2B SaaS platforms to $50M+ ARR Financial services experience - trading systems, risk management, or regulatory compliance AI/ML expertise - LLMs, real-time ML systems, or quantitative finance applications Technical Expertise Deep knowledge of distributed systems, microservices, and cloud architecture Experience with real-time data processing and high-frequency More ❯

millions of data points per second from LSE, Bloomberg, and alternative data sources Autonomous AI Agents: Build intelligent agents for trading, compliance, research, and risk management Predictive Analytics: Develop ML models for earnings prediction, M&A identification, and market regime detection Technical Infrastructure Cloud-Native Architecture: Multi-region deployment (London/Dublin/Frankfurt) with auto-scaling Real-time Data … Integrations: Bloomberg Terminal, Refinitiv, prime brokerage APIs, and regulatory systems Advanced Security: Zero-trust architecture, FCA compliance, and financial-grade security protocols 🔧 Technical Stack You'll Lead AI/ML: TensorFlow, PyTorch, MLflow, NVIDIA Triton, custom financial LLMs Data: Kafka, Flink, Snowflake, ClickHouse, Neo4j, vector databases Backend: FastAPI, GraphQL, microservices, Docker, Kubernetes Frontend: React/Next.js, TypeScript, real-time dashboards … discriminate on age and experience Proven track record building and scaling B2B SaaS platforms to $50M+ ARR Financial services experience - trading systems, risk management, or regulatory compliance AI/ML expertise - LLMs, real-time ML systems, or quantitative finance applications Technical Expertise Deep knowledge of distributed systems, microservices, and cloud architecture Experience with real-time data processing and high-frequency More ❯

millions of data points per second from LSE, Bloomberg, and alternative data sources Autonomous AI Agents: Build intelligent agents for trading, compliance, research, and risk management Predictive Analytics: Develop ML models for earnings prediction, M&A identification, and market regime detection Technical Infrastructure Cloud-Native Architecture: Multi-region deployment (London/Dublin/Frankfurt) with auto-scaling Real-time Data … Integrations: Bloomberg Terminal, Refinitiv, prime brokerage APIs, and regulatory systems Advanced Security: Zero-trust architecture, FCA compliance, and financial-grade security protocols Technical Stack You'll Lead AI/ML: TensorFlow, PyTorch, MLflow, NVIDIA Triton, custom financial LLMs Data: Kafka, Flink, Snowflake, ClickHouse, Neo4j, vector databases Backend: FastAPI, GraphQL, microservices, Docker, Kubernetes Frontend: React/Next.js, TypeScript, real-time dashboards … discriminate on age and experience Proven track record building and scaling B2B SaaS platforms to $50M+ ARR Financial services experience - trading systems, risk management, or regulatory compliance AI/ML expertise - LLMs, real-time ML systems, or quantitative finance applications Technical Expertise Deep knowledge of distributed systems, microservices, and cloud architecture Experience with real-time data processing and high-frequency More ❯

or product analytics with core focus in customer experience (if available) Build and evaluate Generative AI solutions and Large Language Models (LLMs) for various use cases. Develop and implement machine learning models, including predictive, forecasting, classification, and deep learning models. Experience in working with various data sets, including transactional/EPOS, digital, social, loyalty etc. Hands on … experience in using programming languages such as Python Knowledge of cloud platforms and tools for data science and machine learning. Utilise visualization tools such as Power BI or Tableau to present data insights … effectively. Collaborate with cross-functional teams to understand business challenges and create valuables products/solutions Proven project management experience, including planning, execution, and successful delivery of AI/ML POCs, MVPs and production grade solutions. People management skills, including mentoring, guiding, and developing team members. It Would Be a Bonus If You Have Experience in primary growth sectors; CPR More ❯