326 to 350 of 6,120 Machine Learning Jobs in the UK

shelf LLMs, bespoke fine-tuned models, and sometimes techniques that utilise no LLM at all. This means you will Train, evaluate, and iterate on ML models and agentic systems for customer feedback, including owning our custom fine-tuning pipelines. Run experiments end-to-end, track results rigorously, and make clear … collaborate closely with Engineering on productionisation, model serving, data pipelines, and monitoring. Work with Product and Commercial teams to translate business needs into practical ML solutions, and support client evaluations and accuracy benchmarking. Mentor team members, review code and research, and bring relevant advances from the literature into the product. ...

Leadership & Execution: Drive the technical roadmap for Search, Retrieval, Ranking, and Recommendation systems within the Trips vertical. Translate high-level business goals into concrete ML architectures and scalable production systems. Advanced Algorithm Innovation: Design, prototype, and scale next‐generation recommendation and ranking models. Solve complex, non‐linear travel journeys … closely with Product Managers, Engineering Leads, and Data Science peers to optimize multi‐task business objectives simultaneously. Act as the primary technical authority for ML initiatives within the Trips vertical. Talent Multiplier: Mentor and coach senior and mid‐level ML scientists. Foster a culture of technical excellence, driving best practices ...

Leadership & Execution: Drive the technical roadmap for Search, Retrieval, Ranking, and Recommendation systems within the Trips vertical. Translate high-level business goals into concrete ML architectures and scalable production systems. Advanced Algorithm Innovation: Design, prototype, and scale next-generation recommendation and ranking models. Solve complex, non-linear travel journeys … closely with Product Managers, Engineering Leads, and Data Science peers to optimize multi-task business objectives simultaneously. Act as the primary technical authority for ML initiatives within the Trips vertical. Talent Multiplier: Mentor and coach senior and mid-level ML scientists. Foster a culture of technical excellence, driving best practices ...

help lead the design, development, and maintenance of high-quality software solutions Consume and extend our internal machine learning library to surface ML functionality to users through the backend Design and build the scalable, high-performance backend services and APIs that deliver functionality to users, applying security best … similar async Python frameworks) Strong working knowledge of modern machine learning — able to understand, integrate, and extend the functionality of an ML library (NumPy, SciPy, Pandas, and frameworks such as scikit-learn or PyTorch) Understanding of core ML concepts — model training, evaluation, and production trade-offs — enough ...

support of the CODAS project and related R&D Lab initiatives. Contribute to the delivery of technical components for a sovereign AI ecosystem, including ML services, data processing pipelines, evaluation tooling and deployment‐ready applications. Support the translation of research outputs into robust, maintainable and operationally viable systems. Work with … internal colleagues and external project partners to understand technical requirements, constraints and delivery priorities. Help adapt AI and ML approaches to privacy‐sensitive, security‐conscious and regulated deployment contexts. Contribute to the integration of technical solutions into project infrastructure, workflows and partner environments. Troubleshoot technical, data and integration issues arising ...

delivery of machine learning systems at Super Technologies. By combining cutting‐edge applied machine learning, foundational research, and seamless ML operations, the team harnesses data to revolutionize the online gambling and sports betting experience. From predictive analytics and personalization to fraud detection and real‐time recommendations … gaming or entertainment industry Experience working with tools and technologies such as Spark, Snowflake, Qwak, MLFlow, Airflow, etc Contributions to open‐source AI/ML projects or participation in AI/ML competitions (e.g., Kaggle) Experience with training and fine‐tuning large‐scale foundation models (e.g., GPT, BERT ...

generative AI solutions that can move from experimentation into production. You'll work closely with product owners, data engineers, software engineers, and other ML practitioners to design, test, improve, and deploy AI/ML capabilities at scale. This is a hands-on role for someone who enjoys solving technical problems … into reliable systems. Job Responsibilities: Apply machine learning, deep learning, and generative AI techniques to business problems Design, run, and evaluate ML experiments using current tools and frameworks Work with large language models, AI agents, and related methods to enhance ML workflows Write production-quality code ...

tooling for experimentation, evaluation, and debugging; Translate research models into robust, production-ready systems; Monitor and improve model performance in real-world usage. Own ML projects end to end within a product team, including framing the problem, choosing the approach, executing the plan, shipping the feature, and monitoring its performance … production. Work closely with SMB, Scaler, or Enterprise product teams on focused ML problems tied to clear customer and business outcomes. Make build vs. buy decisions for ML models, deciding when to fine-tune or build models versus integrating external models or APIs. Move quickly from idea to production, prioritizing ...

hackajob is partnering directly with Accenture to hire for this role. YOU ARE As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production … include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks experience in building and deploying AI/ML based software to a cloud environment. PREFERRED QUALIFICATION Proficiencyin Python andpython-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow,PyTorch ...

hackajob is partnering directly with Accenture to hire for this role. YOU ARE As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production … include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks Experience in building and deploying AI/ML based software to a cloud environment. PREFERRED QUALIFICATION Proficiencyin Python andpython-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow,PyTorch ...

innovation in this fast evolving space as new technologies reshape how money moves. In this role, you will work at the forefront of modern machine learning and generative AI to deliver meaningful, lasting impact on global finance. You will partner closely with product, operations, risk, and technology teams … measurable outcomes. You will also have opportunities to mentor others and help shape how we build and operate production AI. As a Vice President Machine Learning Data Scientist in Payments Machine Learning, you will lead the design, development, and production deployment of machine learning ...

-learning, product, data and platform partners. This is a hands-on engineering role for someone who can move comfortably between software architecture, ML lifecycle decisions and production operations. You will improve the paths the team uses to train, evaluate, deploy and observe models, while helping us manage latency … including tool routing, retrieval, guardrails and answer caching. Design caching as an intentional latency and cost lever for high-volume services. Build observability for ML and LLM systems, including latency attribution, quality metrics, tracing and per-request cost. Improve the reliability and operability of distributed systems, and lead the diagnosis ...

ReqID:FEQ327R501Location: LondonSkills: Data Science, Machine Learning, AI, LLM, GenAIMissionAs a Senior Specialist Solutions Architect (ML & AI), you will serve as the trusted technical ML and AI expert for Databricks customers and the Field Engineering organization. You will partner with Solution Architects to guide enterprise and strategic customers … architecting production-grade ML and AI applications on the Databricks Data Intelligence Platform. You will also continue to sharpen your technical expertise in cutting-edge areas like GenAI, ML, MLOps, and LLMOps, while mentoring colleagues and establishing yourself as an AI thought leader. Impact you will haveArchitecting Workloads: Design ...

collaborate in person. Our Data EnvironmentOur Data teams are aligned to divisions covering the following Banking Services & Products, Customer Identity & Financial Crime and Data & ML Engineering. Our Data teams are excited about delivering meaningful and impactful insights to both the business and more importantly our customers. Hear from the team … problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good. About the RoleThe ML Projects team is at the forefront of bringing cutting edge machine learning to the core of what we do at Starling. As a software ...

here. Everything that makes you unique is welcome; join us and let’s build what’s next - together! Role Overview We are seeking a ML Ops Engineer to join our Platform Engineering team at Anaplan. In this role, you will design, scale, and maintain high-performance MLOps and LLMOps infrastructure … supporting our cutting-edge AI-infused scenario planning platform. You will work closely with Data Scientists, ML Engineers, and Cloud Infrastructure teams to streamline model training, deployment, and inference while ensuring optimal GPU utilisation, reliability, and cost-efficiency. Your Impact Provision and manage cloud-native AI/ML infrastructure utilising ...

culture in Risk Management and Compliance is all about challenging the status quo and striving to be best in class. As an Applied AI ML Director, Risk Management & Compliance at JPMorganChase within the Digital Strategy and Enablement team, you will be supporting Market Risk, Country Risk and Principal Risk … high-performing team focused on deep data understanding and advanced analytics, driving the development of robust tools and solutions using cutting-edge AI/ML techniques, cloud technologies, and enterprise knowledge bases. In this strategic and hands-on role, you will engage with technical aspects, review code, monitor the impact ...

This space moves fast. We need someone who follows it seriously, brings new ideas back to the team, and actively applies what they're learning to the products we build. If you've been experimenting with new models, new tooling, or new patterns, that's exactly the kind … products and asset classes, with an appreciation of how transactions flow from source product systems to financial reporting Strong working knowledge of Agentic AI, ML, LLM, A2A concepts, Intelligent rule engine and their practical applications in business processes across financial services. Solid Experience with Data pipelines/integrations and consumption ...

MLOps Engineer to join our Data & Compute Platform team based in London. What You’ll Do Own and manage the full lifecycle of both ML models and core infrastructure - from development and deployment to monitoring and continuous improvement. Build and maintain robust CI/CD pipelines for both software … ML workflows. Ensure reliability, scalability, observability, and security of production systems and ML infrastructure. Automate deployment, orchestration, and environment management using modern DevOps tooling. Collaborate closely with software engineers, data scientists, and product teams to bring ML-powered features to production. Proactively detect, troubleshoot, and resolve infrastructure and model performance ...

build what’s next – together! You will join the Predictive Intelligence engineering team within Anaplan, building the backend services that power the ML Engine behind the Syrup platform and Anaplan’s forecasting solutions. The team is responsible for the production execution of forecasting and predictive models, the MLOps infrastructure supporting … services that deliver insights to enterprise customers. This role reports to the Director of Engineering for Predictive Intelligence and works closely with data scientists, ML engineers, and platform partners. Your Impact Design and implement scalable, fault-tolerant predictive intelligence services and features as a core contributor to the ML Engine ...

enjoy turning ambiguity into reliable production systems, you’ll thrive here. Join a team that values craft, security, and learning. As an Applied AI ML Lead in LLM Suite Engineering, you will design and deliver production-grade AI/ML and agentic solutions that integrate seamlessly with existing systems. … algorithms that integrate with existing systems Create architecture and design artifacts for complex applications, ensuring design constraints are met through delivery Build AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworks Implement GenAI services leveraging Azure OpenAI ...

enjoy turning ambiguity into reliable production systems, you'll thrive here. Join a team that values craft, security, and learning. As an Applied AI ML Lead in LLM Suite Engineering, you will design and deliver production-grade AI/ML and agentic solutions that integrate seamlessly with existing systems. … maintain algorithms that integrate with existing systemsCreate architecture and design artifacts for complex applications, ensuring design constraints are met through deliveryBuild AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworksImplement GenAI services leveraging Azure OpenAI models ...

deployment within cloud-based environments Maintain high standards of code quality, documentation, and testing within a DevOps-oriented workflow Apply strong knowledge of ML techniques, from supervised/unsupervised learning through to emerging methods in generative ai and large language models What We’re Looking For: Essential Skills & Experience … across varied data types and business domains Familiarity with DevOps practices and tools such as Git Cloud experience (e.g., Azure, AWS) and working with ML platforms and services Excellent communication skills, with the ability to explain complex concepts to non-technical stakeholders Ability to align analytical outputs with broader business ...

deployment within cloud-based environments Maintain high standards of code quality, documentation, and testing within a DevOps-oriented workflow Apply strong knowledge of ML techniques, from supervised/unsupervised learning through to emerging methods in generative ai and large language models What We’re Looking For: Essential Skills & Experience … across varied data types and business domains Familiarity with DevOps practices and tools such as Git Cloud experience (e.g., Azure, AWS) and working with ML platforms and services Excellent communication skills, with the ability to explain complex concepts to non-technical stakeholders Ability to align analytical outputs with broader business ...

build, and deploy scalable machine learning algorithms and software solutions. Analyse, cleanse, and normalise complex time-series data and dynamical systems. Integrate ML models into production using cloud platforms and modern JavaScript frameworks. Collaborate within an Agile environment to deliver robust data structures and algorithms. What … engineering and data science capabilities: Core Development: Proficiency in Python, JavaScript, and Java, alongside modern frameworks (React, Redux, Vue, or Angular). Data Science & ML: Solid understanding of common ML techniques, trade-offs, and scalable ML architecture (MapReduce, streaming). Data Expertise: Experience with time-series data, dynamical systems ...

data science, contributing expertise across projects, bids and stakeholder discussions Leading and delivering complex machine learning and AI projects in collaboration with ML engineers, delivery teams and customers Engaging with users to define requirements, scope AI use cases and develop realistic delivery plans Supporting the design, development … tabular data Strong Python skills and experience with common libraries (e.g. pandas, NumPy, scikit-learn, PyTorch, Transformers, statsmodels, PyMC) Understanding of software engineering and ML best practices, including version control, packaging and model deployment Experience training and deploying models using cloud platforms, particularly AWS Ability to communicate complex ideas clearly ...