1,851 to 1,875 of 6,391 Machine Learning Jobs in the UK

Responsibilities: Lead the UK Financial Crime ML portfolio, setting technical direction and ensuring high-quality, scalable model delivery across fraud and transaction monitoring use cases. Driveend-to-end model lifecycle ownership — from data exploration and feature engineering to deployment, monitoring, and performance optimisation. Provide hands-on technical leadership, reviewing Python … computing frameworks (e.g., Spark or similar) and scalable data processing environments. Exposure to cloud-based platforms (e.g., AWS, Azure, GCP or Databricks) and modern ML/MLOps practices. Proven track record managing and growing high-performing data science teams, including technical mentoring and delivery accountability. Strong stakeholder management skills, able ...

foster external collaborations with academic and industrial partners Follow scientific and technical standards for experimentation, reproducibility, and model evaluation Collaborate deeply with Engineering, ML Platform, and HPC teams to deliver robust and reliable model updates to users Qualities we look for We're looking for a scientist with a deep … Python and at least one modern machine learning framework such as PyTorch, TensorFlow, or JAX, experience working with large compute clusters and ML infrastructure is a plus. A track record of leading self-directed research projects that go well beyond academic exercises and deliver tangible results. Expertise ...

life-changing medicines with an ambition to solve all disease. The future is coming. A future enabled and enriched by the incredible power of machine learning. A future in which diseases are curtailed or cured starting with better and faster drug discovery. Come and be part of an interdisciplinary … that will transform the biopharmaceutical world as we know it. You'll join our Platform group, where you partner with leading engineers, scientists and ML researchers to build the critical foundations driving that transformation. You'll be working as part of a small and highly efficient team on all parts ...

blog posts, and white papers. You will also have the opportunity to work with our product and engineering teams to build new statistics/ML features for all of Optimizely’s products. You will have also have the opportunity to partner with experts in academia and research to explore … Optimizely should invest in. Job Responsibilities Product and Feature Development Collaborate with product managers and engineering teams to design and implement new statistical and machine learning features across Optimizely’s product suite. Conduct rigorous testing and validation of new statistical methods and ensure seamless integration into the platform. ...

detection measurement framework, defining metrics and evaluation strategies for problems where ground truth is noisy, delayed, or contested. Drive adoption of promising AI/ML techniques and represent Cloudflare in the broader research community. Drive cross-functional partnerships with ML Engineers, Data Engineers, and Product; Influence roadmaps and align detection … problem, and are fluent with large-scale data. You have at least 8-10 years of experience professionally working in Data Science, ML Engineering, or Software Engineering. Demonstrated ability to make ambiguous, high-stakes technical decisions with incomplete information. You are very comfortable with Python & SQL in production environments. Bonus ...

apply even if you only partially fulfil the following lists. You should have: Masters degree (MSc, MEng, etc) in computer science, mathematics, artificial intelligence, machine learning, or a related engineering field 1 year of experience developing agentic AI in production ready environments 3 years of relevant hands … algorithms The ability to write clean and maintainable code in Python, Rust, C++ or Java A strong background in the mathematical foundations of core ML algorithms, paired with hands‐on experience using deep learning frameworks (PyTorch, JAX, TensorFlow), agentic orchestration ecosystems (LangGraph, Google ADK), and Model Context Protocol tooling ...

project delivery, stakeholder engagement, and supporting the development of others. For those at Consultant level, the role offers strong exposure to client work, learning from experienced practitioners, and a clear pathway for progression. We value curiosity, collaboration, and a growth mindset, and we encourage applications from candidates …/EPOS, digital, social and loyalty. AI Delivery Excellence – Proven experience owning workstreams including planning, execution, and successful delivery of insights or AI/ML POCs, MVPs and production grade solutions. Programming Experience - Skilled in using programming languages such as Python Cloud Expertise - Knowledge of cloud platforms and tools ...

leader to define and execute our global Applied AI strategy. You will sit at the intersection of business strategy, engineering, data architecture, AI/ML and enterprise risk management, with accountability for turning AI from isolated experimentation into a scalable, controlled and commercially valuable capability across the group. … value realisation of AI use cases at enterprise scale. What you offer Significant experience in senior technical leadership roles across software engineering, data architecture, machine learning, applied AI, AI platform engineering or related disciplines. Deep understanding of distributed systems, enterprise data architecture, cloud platforms, application programming interfaces ...

projects, including supporting other Data Analysts and Scientists and collaborating with software engineers towards the best solution. You will have a focus on developing ML-centric data products and solutions, in which your expertise with ML frameworks and workflows will be key. Right now, our Data Scientists are working … expect applicants to have experience with all of these):Python and Databricks for Data Science, Spark, MLFlow and Airflow for ML Workflows, Google Cloud Platform for our analytics infrastructure, dbt and BigQuery for data modelling and warehousing. Discover more about our Analytics Community in our blog and explore ...

dynamic and passionate compact team dedicated to creating a SaaS solution to boost eCommerce revenue. We are selected as one of the 25 Machine Learning Startups to Watch by Forbes magazine. We are one of the fastest growing start-ups in AI based e-commerce solutions with multiple … object-oriented fashion Experience designing fault-tolerant, multi-region deployments in cloud environments is a plus Familiarity with recommendation algorithms, ranking, personalization, or ML integration into production microservices Hands-on with Solr/Elasticsearch/OpenSearch for large-scale product search is a plus Strong knowledge and focus on observability ...

Expert – Expert in building and evaluating Generative AI solutions and Large Language Models (LLMs) for various use cases. Experience in developing and implementing machine learning models, including predictive, forecasting, classification, and deep learning models. CX Data Experience - Hands-on experience in customer behaviour analytics, marketing, commercial …/EPOS, digital, social and loyalty. AI Delivery Excellence – Proven experience owning workstreams including planning, execution, and successful delivery of insights or AI/ML POCs, MVPs and production grade solutions. Programming Experience - Skilled in using programming languages such as Python Cloud Expertise - Knowledge of cloud platforms and tools ...

evaluation , implementing rigorous frameworks to continuously monitor, measure, and improve GenAI feature quality, accuracy, latency, and user satisfaction. , Collaborate with data scientists to productionise ML models and forecasting algorithms Your Skills Extensive background in Data Science Engineering, with a clear track record of principal‐level technical leadership. Hands‐on experience … building and shipping AI/ML products in production Deep practical experience with LLM‐based systems: RAG architectures, embedding pipelines, prompt and response logging, evaluation frameworks. Hands‐on expertise with vector databases, graph databases, and knowledge graphs End‐to‐end exposure in model lifecycle development, including extensive experience training ...

post-graduation engineering experience, with demonstrated proficiency in languages such as Python, TypeScript/JavaScript, Java, or C++.2+ years of experience applying AI/ML in production environments, such as deploying deep learning solutions, building generative/agentic AI applications or setting up evaluations pipelinesFamiliarity with cloud-based machine learning tools and platforms (e.g. AWS, GCP, Azure)Strong problem-solving skills, with a data-driven approach to iterating on machine learning models and datasetsExcellent written and verbal communication skills to collaborate effectively in a cross-functional environmentNice to haves: Experience working at a startup, particularly ...

including predictive forecasting and generative or agentic use cases; familiarity with SQL, APIs and modern data-integration technologies, and some exposure to Python or ML platforms (deep engineering isn't required); relevant EPM, cloud-data or AI certifications; and a professional finance or accounting qualification (ACA, ACCA, CIMA or equivalent … including predictive forecasting and generative or agentic use cases; familiarity with SQL, APIs and modern data-integration technologies, and some exposure to Python or ML platforms (deep engineering isn't required); relevant EPM, cloud-data or AI certifications; and a professional finance or accounting qualification (ACA, ACCA, CIMA or equivalent ...

including predictive forecasting and generative or agentic use cases; familiarity with SQL, APIs and modern data-integration technologies, and some exposure to Python or ML platforms (deep engineering isn't required); relevant EPM, cloud-data or AI certifications; and a professional finance or accounting qualification (ACA, ACCA, CIMA or equivalent … including predictive forecasting and generative or agentic use cases; familiarity with SQL, APIs and modern data-integration technologies, and some exposure to Python or ML platforms (deep engineering isn't required); relevant EPM, cloud-data or AI certifications; and a professional finance or accounting qualification (ACA, ACCA, CIMA or equivalent ...

including predictive forecasting and generative or agentic use cases; familiarity with SQL, APIs and modern data-integration technologies, and some exposure to Python or ML platforms (deep engineering isn't required); relevant EPM, cloud-data or AI certifications; and a professional finance or accounting qualification (ACA, ACCA, CIMA or equivalent … including predictive forecasting and generative or agentic use cases; familiarity with SQL, APIs and modern data-integration technologies, and some exposure to Python or ML platforms (deep engineering isn't required); relevant EPM, cloud-data or AI certifications; and a professional finance or accounting qualification (ACA, ACCA, CIMA or equivalent ...

data-driven platforms. Familiarity with cloud infrastructure (Azure, AWS, GCP). Experience working in scale-up environments with evolving priorities. Exposure to ML/AI systems or knowledge-based platforms Benefits of joining us Cutting-Edge Technology: Work with modern AI, from machine learning models to agentic systems … prioritize productivity and work-life balance Real-World Impact: Build AI systems that accelerate global technological innovation Continuous Learning: Opportunities to grow in ML engineering, product design, and systems architecture Hybrid Working: 2-3 days per week from our Shoreditch Please note During periods where we receive very high ...

foster external collaborations with academic and industrial partners Follow scientific and technical standards for experimentation, reproducibility, and model evaluation Collaborate deeply with Engineering, ML Platform, and HPC teams to deliver robust and reliable model updates to users Qualities we look for We’re looking for a scientist with a deep … Python and at least one modern machine learning framework such as PyTorch, TensorFlow, or JAX, experience working with large compute clusters and ML infrastructure is a plus. A track record of leading self-directed research projects that go well beyond academic exercises and deliver tangible results. Expertise ...

Quantitative Trading & Research – Quantitative developer in the AI Market Lab,you will work at the boundary of quantitative research, low-latency engineering, and ML infrastructure, creating reliable platforms that shorten the path from raw market data and research prototypes to monitored, resilient production strategies. We are seeking strong talent … engineering, mathematics, or a related technical discipline (or equivalent professional experience). Relevant professional experience in software engineering, quantitative development, low-latency systems, or ML infrastructure. Strong modern C++ skills in data structures, concurrency, memory management, performance profiling, and production debugging. Proficiency in Python and experience building software for quantitative ...

OpportunityThe 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 to accelerate …/relationship extraction/resolutionKnowledge Graphs; building and inference, graphRAGRecommendation systems and ranking: personalisation, learning-to-rank, feed ranking, user modelling, etc. Tabular ML: feature engineering, structured data modelling (GBDTs, etc.)Statistical & Predictive Modelling: supervised ML, anomaly detection, temporal modelling, etc. Deep understanding of the GenAI landscape and agentic ...

design discussions and supporting client engagements with technical expertise. You will deliver end‐to‐end solutions, from building data pipelines and deploying AI/ML workloads to provisioning infrastructure and automating deployments through CI/CD. This is a London‐based role. Responsibilities Implement, deploy, and maintain Google Cloud infrastructure … maintain data and analytics platforms using services such as BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Composer Implement and support AI/ML platforms on Google Cloud, including Vertex AI, Model Garden, and Gemini‐based tooling, contributing to Agentic AI solutions Support cloud migration and modernisation initiatives using lift ...

looking for? Experience operating as a senior security engineer and leading engineering initiatives in a DevSecOps environment. Strong expertise securing AI and ML systems at scale, including model lifecycle security, data pipelines, and secure deployment. Strong hands‐on experience with machine learning stacks, such as PyTorch, TensorFlow, MLflow … Kubeflow, or equivalent managed platforms (e.g. Vertex AI, Azure ML). Solid understanding of cloud‐native and containerised architectures, including Kubernetes and serverless technologies. Experience operating in complex hybrid environments, spanning public cloud, private cloud and on‐premise platforms. Experience building automation and engineering tooling using Python, Go, or similar ...

maintenance of ETL pipelines, services and APIs, and data-related infrastructure like Redshift or BigQuery; Data Science and Machine Learning: data exploration, ML models training and ML Ops to extract new insights from data; Analytics and Reporting: creation of data models and dashboards as well as automation … Flask API, add unit tests, and deploy the new version of the API into our production Kubernetes cluster; Train and evaluate an ML model to identify certain user patterns and provide it as service to other engineering teams in a Flask API; Team Tech Stack Our current technology stack primarily ...

client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI). Our consultants are at the heart of everything we do, and we have been recertified as a 2025 Great Place to Work … insurance. Life cover. Cycle to work scheme. Eligibility for company pension scheme (5% employer contribution, salary sacrifice option). Employee assistance programme. Bespoke online learning via Udemy for Business. #J-18808-Ljbffr ...

beneath enterprise performance management. You'll shape how EPM platforms stitch together with the modern data platforms finance now runs on, and how machine learning and generative AI make planning and forecasting sharper, faster and more trusted. You'll build real credibility across both finance planning … including predictive forecasting and generative or agentic use cases; familiarity with SQL, APIs and modern data-integration technologies, and some exposure to Python or ML platforms (deep engineering isn't required); relevant EPM, cloud-data or AI certifications; and a professional finance or accounting qualification (ACA, ACCA, CIMA or equivalent ...