526 to 550 of 2,835 Machine Learning Jobs in the UK

design practices. Deep understanding and experience of at least one server-side language. Expertise in cloud-native architectures. Expertise in data pipelines and event-driven architectures preferred. Expertise in machine learning and machine learning pipelines preferred. Expertise in workflow or actor frameworks preferred (e.g. Temporal, Akka) preferred. Solid foundation in secure coding practices. Solid understanding of More ❯

Join us as a Machine Learning Engineer at Barclays, where you'll … develop and implement AI tools using state-of-the-art technologies. As part of our Chief Technology Office, you'll work on testing and deploying the latest AI/ML solutions for our bank. In this role, you'll collaborate with talented engineers to enhance our AI platforms, integrate innovative technologies, and adopt industry best practices, contributing to Barclays' commitment … to making banking simpler, better, and more balanced. To be successful as a Machine Learning Engineer, you should have experience with: Developing or integrating AI/ML applications. Deploying AI/ML systems using GPU resources and integrating databases (e.g., VectorDBs). Backend development using Python. Software development lifecycle using Git, Agile, and test-driven development. Docker/ More ❯

development and related design practices. Deep understanding and experience of at least one server-side language Expertise in cloud-native architectures. Expertise in event-driven architectures preferred. Expertise in machine learning and machine learning pipelines preferred. Solid foundation in secure coding practices. Solid understanding of client-side technology (CSS/HTML/JS) Experience with continuous More ❯

re comfortable being the go-to person for all things automation and can lead independently in a fast-moving environment. Bonus points if you: Have a deep understanding of machine learning, deep learning, and other AI techniques or worked on complex AI or LLM-based systems in the past Have experience in customer service or support environments … Have completed AI-related coursework or certifications, such as machine learning, natural language processing, or prompt engineering - either through formal education (e.g. university courses) or platforms like Coursera, DeepLearning.AI , or OpenAI Have proficiency in programming languages such as Python, R, or Java Have an interest or background in fitness, running or health Are capable of rolling up your More ❯

Overview Work within our clients machine learning team to deploy and optimize models for applications like low-latency speech recognition and large language models (LLMs). Initial focus … will be on improving our clients speech recognition model's training pipeline on multi-GPU systems to boost performance and quality. Responsibilities: Train and deploy state-of-the-art ML models. Apply optimization techniques (distillation, pruning, quantization). Enhance speech models with features such as diarization, multilingual support, and keyword boosting. Optimize models for low-latency inference on accelerators. Improve … training workflows and GPU utilization. Use data augmentation to improve performance. Stay updated on ML research to guide strategy. Requirements: Master's or PhD in a relevant field with strong ML foundations. Training ML models for production use. PyTorch or TensorFlow. Handling large datasets (multi-terabyte). Familiarity with Linux, version control, and CI/CD systems. Knowledge of model More ❯

and big data platforms worldwide, processing some 600B events every day and making some 5B predictions. As part of the Data Science and Machine Learning (AI/ML) team you will be exposed to real-world challenges such as: dynamic pricing, predicting customer intents in real time, ranking search results to maximize lifetime value, classifying and deep learning … partners, discovering insights from big data, and innovating the user experience. To tackle these challenges, you will have the opportunity to work on one of the world's largest ML infrastructure employing dozens of GPUs working in parallel, 30K+ CPU cores and 150TB of memory. In This Role, You'll Get to Design, code, experiment and implement models and algorithms … Research discover and harness new ideas that can make a difference. What You'll Need To Succeed 4+ years hands-on data science experience. Excellent understanding of AI/ML/DL and Statistics, as well as coding proficiency using related open source libraries and frameworks. Significant proficiency in SQL and languages like Python, PySpark and/or Scala. Can More ❯

We are looking for an engineer with experience in low-level systems programming and optimisation to join our growing ML team. Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction. … problems, we have a feeling youll fit right in. Theres no fixed set of skills, but here are some of the things were looking for: An understanding of modern ML techniques and toolsets The experience and systems knowledge required to debug a training runs performance end to end Low-level GPU knowledge of PTX, SASS, warps, cooperative groups, Tensor Cores More ❯

Senior Machine Learning Scientist (Viator) London, England, United Kingdom About Viator Viator, a Tripadvisor company, is the leading marketplace for travel experiences. We believethat making memories is what travel is all about. And with 300,000+ travel experiences toexplore-everything from simple tours to extreme adventures (and all the niche, interesting stuffin between)-making memories that will last … embedding, Recommendation Systems, and Computer Vision. To be successful in the role, you'll need: 5+ years of hands-on data science experience. In-depth knowledge of AI/ML/DL, Statistics, and related open-source libraries. Awareness of current ML techniques, keen on self-improvement and striving to solve real-world data challenges. Strong skills in SQL and … at least one programming language. Experience in ML model productization and a grasp of MLOps. To be comfortable in code reviews, discussing architecture, and collaborating with a multidisciplinary team for regular model deployments. Experience in deploying online solutions and analysing real-time results through A/B testing. To be passionate about mentoring junior members of the team, and have More ❯

emerging AI trends and industry best practices to drive innovation and deliver cutting-edge solutions. Connect to your skills and professional experience Technical Proficiency: Strong understanding of AI concepts, machine learning algorithms, and deep learning architectures. Familiarity with various AI solution design patterns and best practices for different … business applications. Experience with data visualization tools and techniques to communicate insights and solution designs effectively. Knowledge of cloud computing platforms (e.g., AWS, Azure, GCP) and their AI/ML services. Basic understanding of programming languages like Python and R is beneficial. Education and Experience: Bachelor's or Master's, or equivalent degree in Computer Science, Data Science, Business Analytics … with a focus on AI and data-driven solutions. Deep experience in the financial services industry. Strong problem-solving, analytical, and communication skills. Relevant industry certifications (e.g., AWS Certified Machine Learning - Specialty, Azure AI Fundamentals or equivalent) are a plus. Connect to your business - Technology and Transformation Distinctive thinking, deep expertise, innovation, and collaborative working. That's what More ❯

a Senior CFD engineer, you won't just create models, you'll build what truly matters. This Role In this role, you'll work closely with our Data Scientists, Machine Learning Engineers, and customers to understand and define the engineering and physics challenges we are solving. You'll play a crucial role in delivering high-fidelity simulations by … accuracy and efficiency, often working under pressure to meet tight deadlines. - Working at the intersection of CAE and data science, generating accurate simulation results and predictions to train advanced Machine Learning and Deep Learning models. - Continuously improving engineering practices, adapting CAE model setups and outputs to support the development of Deep Learning surrogates. - Mentoring junior engineers … for you. Hybrid setup - enjoy our new Shoreditch office while keeping remote flexibility. Enhanced parental leave - support for life's biggest milestones. Private healthcare - comprehensive coverage Personal development - access learning and training to help you grow. Work from anywhere - extend your remote setup to enjoy the sun or reconnect with loved ones. We value diversity and are committed to More ❯

parent company? Thats what you would be doing if you joined Amex GBT. The team's responsibilities include data integration supporting customers and internal business areas, as well as ML platform development. We are seeking a talented individual with a diverse skill seta passionate technologist dedicated to solving real-world business problems; to lead the excellence of Data/ML … development lifecycle. Collaborate with key partners and contribute expertise to develop unique solutions to complex issues. Have good infrastructure knowledge (AWS, Kubernetes). Experience with Data (BI, Reporting, Analytics, Machine Learning) is a plus. What Were Looking For 2 to 3 years for Bachelor's or equivalent/for Master's Development background, infrastructure (AWS) knowledge, Data awareness … Experience in data modeling, schema design, data access patterns (API, streaming, data lake), and AWS Familiarity with cloud technologies and building data products supporting batch and real-time DS, ML, and Deep Learning applications. Ability to design and communicate architecture for data products. Understanding of testing and monitoring tools and technologies. Guide others in designing testable and observable software. More ❯

can have equal and unconstrained access to educational experiences on par with Oxford, Cambridge, CalTech, et cetera. We believe that this can be achieved with a new class of learning tools, which combine advances in cognitive science, language models, and datasets. We are building these tools in England. Our first product, Grasp Concepts , enables students to disambiguate and learn … concepts through great online explanations and is deployed with design partners including Imperial College London. Our second product, Grasp Pathways , decomposes learning goals and suggests flexible learning trajectories to reach them, using reputable learning resources like books and lectures, and is in private alpha. An on-demand, online oxbridge-like experience . Team and Funding We've … the best. R&D Engineering at Grasp This is a system design, prototyping, and development role, with a high degree of individual contribution. The systems you build will involve machine learning, generative AI, and applied maths (e.g. graph algorithm) approaches as you solve problems for online self-directed learners. As an individual contributor, you will be expected to More ❯

You will work alongside some of the brightest minds in AI research and engineering in developing impactful solutions that are reshaping the world of regulatory compliance. Role Overview: As ML Engineer, RegBrain, your mission is to: Participate in the continuous improvement of RegBrains products. Develop advanced NLP and AI-based products that will delight users. Provide excellence in cloud-based … ML engineering, with as much focus on Operations as Development. Expand of the Teams knowledge via demonstration and documentation. Key Responsibilities: As a machine learning engineer, your main responsibility is to conduct the development andproductionisationof ML and NLP-based features for CUBEs products - a SaaS Platform (RegPlatform) and an API (RegConnect). Develop optimal ML & NLP solutions for … to SOTA approaches, wherever appropriate. Produce high quality, modular code, and deploy following our established DevOps CI/CD and best practices. Improve the efficiency, performance, and scalability of ML & NLP models (this includes data quality, ingestion, loading, cleaning, and processing). Stay up-to-date with ML & NLP research, and experiment withnew models and techniques. Perform code-reviews for More ❯

have with our clients and with the communities in which we work and live. It is personal to all of us." - Julie Sweet, Accenture CEO Qualification Key responsibilities • Deploy machine learning models to production and implement measures to monitor their performance • Implement ETL pipelines and orchestrate data flows using batch and streaming technologies based on software engineering best … or Kubernetes o Experience with Infrastructure as Code tools (e.g. Terraform or CloudFormation) • Strong understanding of data modelling and system architecture • Demonstrable experience on at least one AI/ML project • Knowledge of common machine learning frameworks and models • A good understanding of approaches to monitoring ML models in production As a technology consultancy, we look for people … their best work. At Accenture, we see well-being holistically, supporting our people's physical, mental, and financial health. We also provide opportunities to keep skills relevant through certifications, learning, and diverse work experiences. We're proud to be consistently recognized as one of the World's Best Workplaces. Join Accenture to work at the heart of change. Visit More ❯

Moogsoft, BigPanda, or IBM Watson AIOps. Programming : Proficiency in languages such as Javascript, Python, Java, and Bash. Cloud Native Expertise : Experience with Docker, Kubernetes, AWS, Google Cloud, or Terraform. Machine Learning : Understanding of machine learning concepts and frameworks. Problem-Solving : Strong analytical and problem-solving skills to address complex IT issues. At McDonald's we are More ❯

high data quality, compliance, and consistency. Develop Scalable Data Models: Collaborate with analysts and data scientists to design and maintain data models that enable more intuitive use for reporting, machine learning, and advanced analytics. Research and Adopt Emerging Data Technologies: Stay ahead of industry trends by researching emerging tools and frameworks. Recommend and lead the adoption of innovations … technical background, ideally with a degree in mathematics, physics, computer science, engineering, or a related field. Understanding of data science concepts and experience collaborating with data scientists to productionise machine learning models. Active participation in tech or open-source communities, with a passion for sharing knowledge and inspiring others. Strong communication skills, with the ability to translate complex … your salary goals with your application. We routinely benchmark salaries against market rates, and run quarterly performance and salary reviews. The culture At iwoca, we prioritise a culture of learning, growth, and support, and invest in the professional development of our team members. We value thought and skill diversity, and encourage you to explore new areas of interest to More ❯

and scientist peers, and build consensus on larger projects, factoring complex efforts into independent tasks that can be performed by you and others. BASIC QUALIFICATIONS - 3+ years of building machine learning models for business application experience - PhD or Master's degree and 6+ years of applied research experience - Experience programming in Java, C++, Python, or related language - Experience … with neural deep learning methods and machine learning - Experience with prompting techniques for LLMs PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, etc. - Experience with large scale distributed systems such as Hadoop, Spark, etc. - PhD in math/statistics/engineering or other equivalent quantitative discipline - Experience with More ❯

experience where manual interventions are needed. The team leverages state-of-the art technology and GenAI to deliver the products and associated goals. BASIC QUALIFICATIONS - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 6+ years of applied research experience - Experience programming in Java, C++, Python or related language - Experience … with neural deep learning methods and machine learning - Experience with prompting techniques for LLMs PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - PhD in math/statistics/engineering or other equivalent quantitative discipline - Experience with More ❯

Daniel Blackwell on: Location: UK Remote Tyne and Wear Newcastle upon Tyne NE12 8BX A leading company is looking foran AI Engineer to drive the integration of AI and machine learning into their products. This role sits at the intersection of AI research, product strategy, and engineering, transforming complex AI concepts into real-world applications. Key Responsibilities: Develop … teams to ensure successful AI implementation. Translate business requirements into technical solutions. Manage relationships with AI vendors and industry partners. What You'll Bring: Degree in Computer Science, AI, ML, or a related field. Experience in developing and deploying AI/ML solutions. Proficiency in Python and ML frameworks (TensorFlow, PyTorch). Strong understanding of LLMs, NLP, and machine learning algorithms. MLOps knowledge and experience with version control systems. Back-end engineering skills in Python or Node.js (willingness to upskill in Node.js/TypeScript). Ability to explain AI concepts to technical and non-technical stakeholders. Problem-solving mindset and ability to lead AI-driven initiatives. Bonus Skills: Experience with AWS and cloud-based AI solutions. Knowledge More ❯

with our clients and with the communities in which we work and live. It is personal to all of us.” – Julie Sweet, Accenture CEO Job Qualifications Key responsibilities Deploy machine learning models to production and implement measures to monitor their performance Implement ETL pipelines and orchestrate data flows using batch and streaming technologies based on software engineering best … Docker or Kubernetes Experience with Infrastructure as Code tools (e.g. Terraform or CloudFormation) Strong understanding of data modelling and system architecture Demonstrable experience on at least one AI/ML project Knowledge of common machine learning frameworks and models A good understanding of approaches to monitoring ML models in production As a technology consultancy, we look for people More ❯

databases and geospatial data formats. Problem-Solving: Strong problem-solving skills and attention to detail. Teamwork: Excellent communication and collaboration abilities. Cloud Solutions: Experience with cloud-based GIS solutions. Machine Learning: Knowledge of machine learning applications for geospatial data. DevOps: Familiarity with DevOps practices and CI/CD pipeline Location: Able to workin the Bath office. More ❯

Spotify's Commerce Platform to build the next generation of our robust, high-performing, and resilient payments ecosystem. This is a unique opportunity to solve complex challenges, work with ML-powered systems, and contribute to the core of Spotify's revenue-generating systems. As part of Spotify's Commerce Platform, we in the Pay-In domain own the critical backend … journey. You will join one of the sub-teams in the Pay-In domain, which develops and maintains the systems that integrate with payment providers, manage disputes, and leverage ML for fraud detection and prevention. The reliability of these systems is business-critical for Spotify. What You'll Do Architect, design, and implement highly scalable backend services (Java/Python … and robust data pipelines that power Spotify's internal Commerce platform. Develop and enhance our ML-powered systems taking solutions from concept to production. Take the lead on API design, platform development, and ensuring the scalability, reliability, and performance of our services. Collaborate with a talented, cross-functional team of engineers, product managers, and data scientists to deliver impactful solutions. More ❯

directly to the resilience of Spotify's global revenue ecosystem. We are all passionate about what we do and move forward with high impact projects at a high pace. Learning and improving is part of our daily routine, and you will be free to develop your skills and ways of working. Our collaborative environment encourages innovation and continuous improvement … Apply your domain knowledge in payments and fraud to inform detection strategies and partner with stakeholders to evolve Spotify's fraud & misuse mitigation approaches. Leverage your deep expertise in machine learning to inform model development, evaluation, and performance monitoring. Monitor and communicate key performance indicators to track the impact of Revenue Protection initiatives and surface emerging risks and … another quantitative field. Proven leadership experience, either as a people manager or mentor, inspiring others and shaping project direction. Hands-on expertise with machine learning, including applying ML to real-world fraud prevention or misuse detection problems. Proficient in Python and SQL. Experience with Google BigQuery is a plus. Familiarity with dashboarding and data visualisation tools such as More ❯

General Theory for Big Bayes" and Grenoble IDEX. Interested applicants should write to us with: a letter of interest, CV, and should require two recommendation letters. Context Bayesian deep learning brings together two of the most important machine learning paradigms: Bayesian inference and deep learning. On the one hand, Bayesian learning provides a theoretically sound framework … to formalise the estimation of the architecture and the parameters of deep neural network models. On the other hand, deep learning offers new tools in Bayesian modelling, e.g. to learn flexible nonparametric priors or computationally efficient posterior distribution approximations. State of the art The field of machine learning has recently been much impacted by deep learning. Deep … for their many parameters to be accurately estimated. Bayesian statistics offers a theoretically well-grounded framework to reason about uncertainty, and it is one of the cornerstones of modern machine learning. At the same time, the theory at the basis of deep neural networks is not yet very well understood and its grounds must be laid out. Although the More ❯

drive strategic business decisions . Gavin developed Rightmove's Automated Valuation Model, used daily by major UK lenders, and has since led the design of GIS platforms, patent-pending ML algorithms, and cloud-native ML pipelines across sectors. With deep experience in modelling, mapping and modern ML tooling , he brings precision, creativity and a delivery mindset to complex data problems. … broader participation and creating new opportunities for merchants and consumers alike. Tech Stack Highlights Cloud-native on GCP with extensive use of BigQuery and Cloud Run Extensive use of ML modelling and LLM inference - no gimmicks here, this is our daily routine Python, Rust and TypeScript - we keep things simple but use the right tool for the job Cross-platform … work, Friday office lunch, covered Uber home and dinner for late nights, and more). Fast and Focused Hiring Process Talent Acquisition Interview - 30 min Technical Deep Dive - Python, ML Tooling, Modelling - 1 hour Case Study Interview - 1.5 hours Relay Operating Principles & Impact- -1 hour Decision and offer within 48 hours . Our process mirrors our pace of work. Relay More ❯