276 to 300 of 5,522 Machine Learning Jobs in the UK

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 ...

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 ...

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 ...

complete the application to adjustments@depop.com. Role Depop is looking for a Staff Machine Learning Scientist to join our new Core ML team in the UK. You will work alongside a multi-functional team of Product Managers, ML Engineers, and fellow ML Scientists, helping build and maintain foundational … evolve them as shared systems Partner closely with senior stakeholders across the business to define problems, and lead the design of general-purpose, scalable ML solutions that power features like content understanding, moderation, and personalisation Lead the end-to-end lifecycle of large-scale experiments, from hypothesis generation through evaluation ...

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 ...

effective AI solutions. This is a hands-on technical leadership role, ideal for someone currently operating as a Lead AI Architect, Principal AI/ML Engineer, AI Engineering Lead, Principal Architect, AI Practice Lead or similar , and looking to take the next step into an Associate Director-level position. … public sector environments. Lead the development and deployment of production-grade Generative AI and Machine Learning solutions. Architect systems integrating LLMs and ML models into wider enterprise applications and workflows. Oversee the full technical lifecycle, from solution design and model selection through to deployment, monitoring and continuous improvement. ...

build production‐ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills. Your Impact Lead the architecture, design, and deployment of scalable Generative AI and Machine learning systems into production environments. … production environments Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour Collaborate with data scientists to productionise ML models and forecasting algorithms Your Skills Extensive hands‐on professional experience in the field of Artificial Intelligence, Machine Learning, or related engineering domains. ...

financial problems Implement guardrails, validation frameworks, and monitoring systems for AI applications Data Engineering & Integration Design and build data pipelines to support AI/ML workflows, integrating market data, trade data, and research content Develop ETL processes for preparing training data and maintaining knowledge bases Create APIs and microservices … governance requirements Stay current with emerging AI technologies and evaluate its applicability to Global Rates business needs Contribute to the firm’s AI/ML community of practice and knowledge sharing initiatives Required Qualifications Education Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning ...

excellence Drive high-quality scientific research and innovation. Publish and present methods and findings internally and externally; contributefirst- or last-author publications in leading ML and clinical AI journals where appropriate. Mentor junior scientists and contribute to developing best practices within the organisation. Stay at the forefront of advances … Systems Biology, or a closely related quantitative discipline - with a strong, hands-on computationaltrack record. Demonstrated experience of high-impact application of AI/ML methods to biological, translational, or clinical data. Deep knowledge of one or more areas of modern AI: foundation model training and fine-tuning adaptation (e.g. ...

between traditional predictive algorithms and modern generative systems. Your Impact Advanced Modeling & Predictive Analytics: Lead the research, design, and implementation of advanced Machine Learning, Deep Learning, and Timeseries Forecasting models to solve complex enterprise business and planning challenges. Generative AI Architecture: Architect GenAI solutions, focusing on fine … Familiarity with Anaplan or similar enterprise planning platforms. Experience with A/B testing and experimentation frameworks for AI features. Contributions to open‐source ML projects or research publications. Our Commitment to Diversity, Equity, Inclusion, and Belonging (DEIB) We believe at Anaplan that diversity, equity, inclusion and belonging are central ...

being written. Key Responsibilities Define and drive the AImethodologyroadmap for assignedClinical AIprogrammes, spanning early and late phase clinical development, and aligning AI/ML priorities with clinical and businessobjectives. Lead, by matrix influence and scientific authority, the delivery of the most complex and high-stakes AI projects — from problem definition … decision-making atprogrammelevel. Shape the AI evidence componentfor regulatory submission packages; act as the scientific and methodological voice in regulatory engagements involving AI/ML methods or innovative trial designs (FDA, EMA, MHRA). Evaluate and championcutting-edgeAI methodologies — including foundation models, agentic AI systems, generative patient models, multimodal learning ...

Responsibilities Define and drive the AI methodology roadmap for assigned Clinical AI programmes, spanning early and late phase clinical development, and aligning AI/ML priorities with clinical and business objectives. Lead, by matrix influence and scientific authority, the delivery of the most complex and high-stakes AI projects — from … programme level. Shape the AI evidence component for regulatory submission packages; act as the scientific and methodological voice in regulatory engagements involving AI/ML methods or innovative trial designs (FDA, EMA, MHRA). Evaluate and champion cutting-edge AI methodologies — including foundation models, agentic AI systems, generative patient models ...

threats. The organisation combines cybersecurity expertise, proprietary solutions, and technology partnerships to deliver tailored security services across various sectors. The organisation is seeking an ML Research Engineer to join its Innovation & Research team and help develop AI-powered security operations capabilities. This role focuses on building and evaluating … agentic systems, improving machine learning models and workflows, analysing performance, and researching security challenges such as adversarial attacks and offers the opportunity to work on cutting-edge AI technologies, influence product development, and collaborate with researchers, engineers, and security specialists. Responsibilities Designing and building evaluation frameworks ...