1 to 25 of 121 Machine Learning Jobs in the City of London

minded with good business acumen alongside technical ability? Hold a Bachelor’s or Master’s degree in Computer Science, Data Science or AI/ML Engineering? Proven experience with Azure Databricks and other Azure services such as Azure ML and AI Foundry? Legal Sector Experience? (Ideal but not essential … products, machine learning models, and agentic AI workflows. Leveraging the Azure ecosystem, the role will focus on delivering production-ready AI/ML infrastructure and applications that are scalable, secure, governed, and cost-effective. The AI Engineer will support the development of Data & AI products that accelerate ...

Data Scientist, London/Oxford hybrid working Are you excited by the opportunity to use machine learning, NLP, and generative AI to help researchers discover knowledge faster and make better decisions? Would you enjoy turning complex scientific and business challenges into practical, production-ready AI solutions that create … strive to maintain. Our team values trust, respect, collaboration, agility, and quality. About the Role In this role, you will design and build machine learning, NLP, and generative AI solutions that support scientific discovery, knowledge extraction, decision support, and intelligent content understanding. You will work with large-scale ...

global leading business is hiring a Senior Machine Learning Engineer. Hybrid position. Paying up to £1000 per day. Outside IR35 Experience and skills required for the Senior Machine Learning Engineer, Quantisation, PEFT, DeepSpeed, ONNX, TensorRT, PyTorch, multi-LoRa, LoRA Exchange, TitanML ️ In depth experience with … following Machine Learning: Quantization, PEFT, DeepSpeed, ONNX, TensorRT Deep Learning with PyTorch Experience with Strong experience working with inference servers like multi-LoRa, LoRA Exchange, TitanML ️ Previous industry exposure to multi-node HPC clusters ️ Experience with Large language models - OpenAI, Mistral, Claude, LLaMA Large language model ...

client's organization, the Data Science team tackles complex business challenges across various domains, including customer experience, supply chain, and technology. They leverage advanced machine learning, generative AI, and large language models (LLMs) to optimize prices, enhance store operations, and personalize customer experiences. Team members enjoy a collaborative … expand their expertise and make a significant impact. Your Role: As a Data Scientist, you'll be at the forefront of developing and deploying machine learning solutions that transform decision-making processes. Your key responsibilities will include: Designing and implementing robust models to optimize business operations. Building ...

influence the technical roadmap, and work directly with experienced founders and a senior engineering team. What you'll be doing: Designing, building and deploying ML-powered features across a production platform Working across Python and TypeScript, integrating models into scalable, real-time systems Fine-tuning and training NLP models using … best practices from the ground up Collaborating closely with product, engineering, and leadership What we're looking for: Strong commercial experience building and deploying ML models in production Proficiency in Python and familiarity with TypeScript/JavaScript Experience with NLP or recommendation systems is a bonus Excited by start ...

involves exploratory data analysis, predictive modelling, and collaboration with cross-functional teams to deliver actionable insights. This position focuses on applying statistical techniques and machine learning methodologies to improve business performance, with opportunities for continuous learning in a fast-paced environment. Key Responsibilitie sPerform exploratory data analysis … driven decision-making app roachDemonstrated continuous learning mi ndset Additional Requirements (Mand atory)Hands-on experience in PythonExperience in Azure and Databricks and ML model development & Depl oymentExperience in Tableau or similar visualisation tools ...

impact. You will also collaborate across teams to turn complex challenges into practical, production-ready solutions. Responsibilities Design, build, and evaluate advanced AI/ML, NLP, and generative AI solutions for scientific and knowledge-discovery applications. Develop LLM-powered workflows and retrieval-augmented generation (RAG) systems for search, summarization, question … experience in data science, AI, machine learning, NLP, information retrieval, or a related quantitative field. Strong hands-on experience building AI/ML, NLP, generative AI, and retrieval-based systems in applied or product-focused environments. Expertise working with LLMs, including fine-tuning, prompt engineering, grounding strategies ...

that is reimagining how future data, engineering and AI professionals are trained before deploying into enterprise client environments. We are looking for a Technical Learning Experience Designer/Technical Curriculum Designer who can design innovative, practical and engaging learning programmes across data engineering, data science, machine learning … also demonstrate you understand how modern data and AI systems are built and applied in industry. The role will involve: Designing end-to-end learning journeys for aspiring data and AI professionals Translating complex technical concepts into engaging modules, workshops, labs and assessments Creating project-based learning experiences ...

deep technical expertise with leadership and stakeholder engagement to deliver scalable, production-ready systems. The ideal candidate will bridge the gap between cutting-edge machine learning and real-world applications … working closely with cross-functional teams to translate requirements into impactful AI solutions. Key Responsibilities Lead the design, development, and deployment of AI/ML solutions from concept to production Architect scalable systems and ensure reliability, performance, and maintainability Collaborate with data scientists, engineers, and business stakeholders to identify ...

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 ...

capability) who have real, hands-on experience building GenAI applications end-to-end. Not just prototypes, but production systems. This is a full-stack ML Engineering role where youll design, build, deploy, and monitor GenAI applications that integrate LLMs as part of a wider system. Youll be working on: Building … stack: data, model, application, and infrastructure Strong communication skills and ability to work with product, engineering, and business teams This is ideal for ML Engineers who love building end-to-end systems, not just models. People who can take a GenAI idea from concept to production and own the full ...

largest real-time fraud detection platform to craft solutions for our enterprise customers. About the role: Your experience with data analysis, statistical modelling, and machine learning will lead to immediate real-world impact in the form of lower customer friction, reduced fraud losses and as a result, increased … machine learning model development, evaluation, and production deployment, with familiarity in MLOps principles to build scalable and standardised workflows and implement effective ML monitoring systems Proven ability to create polished presentations and effectively communicate insights to customers with attention to detail Have extensive multi-tasking and prioritisation skills. ...

ML Ops Engineer Role Overview Were hiring an ML Ops Engineer to own the reliability, scalability, and operational integrity of our machine-learning systems in research & production. This role sits at the intersection of data engineering and ML infrastructure: youll design and operate data pipelines that feed models … with clear SLAs, reproducibility guarantees, and observable behaviour. This is not a research role; it is a hands-on engineering role focused on making ML systems work reliably at scale. What Youll Work On ML lifecycle infrastructure Productionizing models: packaging, deployment, versioning, and rollback Designing CI/CD pipelines ...

APPLIED ML SCIENTIST | REINFORCEMENT LEARNING Build Reinforcement Learning Systems For The Real World 📍 £80k – £110k 💰 London, Hybrid Why is this exciting? Because this sits at the convergence of several areas that are becoming increasingly important: Reinforcement Learning Physical AI Digital Twins & Simulation Federated Learning Edge … push the boundaries of what AI can actually do. Experience required: Strong hands-on experience with Reinforcement Learning (RL) Python and modern ML frameworks ( PyTorch, JAX, TensorFlow ) Experience working with time-series or sensor data Ability to turn real-world problems into practical ML solutions Comfortable taking models from ...

actively to codebases and architectural decisions Developing and deploying production-grade AI systems using Azure, Databricks and Generative AI tooling Owning the implementation of ML pipelines, APIs and data integration workflows Enforcing MLOps best practices, coding standards, version control and performance optimisation Collaborating cross-functionally with data scientists, product managers … Python proficiency (async programming, concurrency, multithreading) Expertise in RESTful API design, OpenAPI/Swagger documentation and API lifecycle best practices Hands-on experience with ML libraries: PyTorch, PySpark, scikit-learn, Hugging Face Transformers Proficiency in AI tooling: Azure ML, Databricks, MLflow, LangChain, LangGraph Proven experience with Git, unit testing, containerisation ...

ML Ops Engineer Role Overview Were hiring an ML Ops Engineer to own the reliability, scalability, and operational integrity of our machine-learning systems in research & production. This role sits at the intersection of data engineering and ML infrastructure: youll design and operate data pipelines that feed models ...

responsible AI solutions across a range of high-profile client engagements. Key responsibilities will include: * Designing and implementing end-to-end AI/ML solutions from development through to deployment and monitoring * Building scalable Generative AI and Agentic AI solutions, including RAG pipelines and orchestration frameworks * Implementing MLOps frameworks, governance … major Consulting firm, and/or in industry * A strong consulting mindset with experience engaging senior stakeholders * Proven experience designing and delivering AI/ML solutions at scale * Strong understanding of Generative AI, Agentic AI and modern AI engineering frameworks * Experience with at least one major cloud platform including Azure ...

Based) Oliver Bernard are currently working with an AI scale up client of ours who are looking for a seasoned Senior/Lead ML Platform Engineer to join their team as part of broad expansion plans across the business. A tight knit team who are changing the way things … done in their industry, they're looking for someone to step into their ML Platform function to lead, drive, and be autonomous in their ways of working - proactively tackling sophisticated challenges whilst transforming and scaling their efforts across Cloud Infrastructure, Containerisation and more! To be suitable for this position ...

ML Researcher Location: London (Hybrid) The Company My client is a fast-growing technology business doing genuinely impactful work, building platforms that make physical environments safer and more intelligent. They operate at the cutting edge of computer vision and real-time AI, and they are scaling quickly. The team … where the work matters and the people are given the space to do it well. The Role They are looking to bring on an ML Researcher to join the machine learning team in London. You will own research directions end-to-end, from problem formulation through to production ...

approach to typical projects that Data Science Consulting Team works on Research, develop, and test solutions to problems that use both supervised and unsupervised learning models Discuss technical and analytical aspects of your work with clients Maintain and improve our machine learning pipelines, processes and products … Sales and Market Research Teams in the US and UK Have knowledge of a Broader set of techniques available for each type of ML problem. Typically having real in-depth knowledge in a couple of areas (e.g. Forecasting, Segmentation etc.). Critically think about what features are required to address ...

production AI company who are seeing fantastic growth. They are seeking a senior python engineer/senior python developer with strong recent AI/ML development experience, to help build production-grade AI systems that power complex, real-world operations. This is not a research role: we’re looking … nce6+ years building production systems in Python, as a Senior Python Engin eerFollowed by strong recent experience (1-2 years+) integrating LLMs or advanced ML models into live products - production level hosting is required, not just local deploym entStrong backend/API development experience, ideally with Fast APIUnderstanding of model ...

different angle on familiar challenges - all without locking you into a single path. Skills we are looking for Strong understanding of artificial intelligence and machine learning concepts, including supervised and unsupervised learning, large language models (LLMs), generative AI, and their practical application and associated risks within financial … bias and fairness assessments, and the design and evaluation of oversight and accountability structures for AI systems. Demonstrable experience auditing or reviewing AI and machine learning models, including model validation, explainability, performance monitoring, data quality and integrity, and the adequacy of model documentation and change management processes. ...

Tech environment Key technologies include: Python Azure Databricks Generative AI/LLM frameworks Agentic AI tooling and orchestration frameworks LangChain/LangGraph PyTorch and ML libraries REST APIs Docker and containerisation CI/CD pipelines Git-based development workflows What we're looking for 4-6 years' experience within Software … Engineering, AI Engineering, or Machine Learning Engineering roles Strong hands-on Python engineering capability Experience building AI or machine learning solutions within production environments Strong understanding of Generative AI and modern AI engineering practices Exposure to Agentic AI frameworks or autonomous AI workflows Experience working with ...

Data Scientist LOCATION- London (Hybrid) TERM- Permanent SALARY- £50,000 to £75,000 per annum BENEFITS – Bonus, Pension, Private Healthcare, Hybrid Working, Learning & Development Budget, Flexi-time etc. We are a well-established consumer-facing organisation with a strong focus on delivering exceptional customer experiences through data-driven decision … London office. The Data Scientist MUST have: • Commercial experience within Data Science, Advanced Analytics, Statistical Analysis, or a related field • Strong experience applying machine learning techniques to solve real-world business problems • Proficiency in Python and SQL for data analysis, modelling, and data manipulation • Experience working with large ...

transform, and distribute sensitive healthcare data originating from Electronic Health Record (EHR) systems, medical devices, and hospital information systems. Working closely with backend engineers, ML engineers, clinical teams, and customer integration partners, you will ensure the reliable, secure, and compliant flow of patient data across operational and analytical systems. Your … Take ownership of operational databases and analytical data warehouses. Design schemas and transformations that support both real-time application requirements and downstream analytics and ML workloads. Optimise performance, cost, and scalability across cloud-based data platforms. Cloud Deployment & Operations Deploy and operate data pipelines and services in AWS. Implement monitoring ...