401 to 425 of 2,703 Machine Learning Jobs in London

quality, observability, and governance into the core of our data ecosystem. This role is critical in ensuring that data powering analytics, trading insight, and machine learning is consistent, well-understood, and fit for purpose. What You’ll Do Design and implement scalable data quality frameworks across batch … similar). Exposure to metadata and governance tooling (e.g. OpenMetadata, Hive Metastore). Understanding of data contracts and schema evolution practices. Experience supporting machine learning or analytics data quality requirements. Why This Role Matters Data quality is foundational to how we operate our sportsbook. This role ensures that ...

machine learning that drives decisions across a 4M+ member platform Build commercial models spanning retention, recommendations and customer growth Work directly with senior stakeholders in a growing Data Science team Up to £90,000 + 7% Bonus Hybrid | London (2 days/week) - Leicester office visit once … forecasting and marketing mix models Detect fraud, broken journeys and offer issues Design and evaluate A/B tests Translate business problems into scalable ML solutions Tech stack: Python, SQL, Databricks, dbt, MLflow Requirements 5+ years' commercial Data Science experience Strong Python and SQL skills Experience with customer, marketing, ecommerce ...

systems for ambitious enterprise clients, working on hard problems: real-time systems operating at significant scale, complex integration landscapes, and platforms where data and machine learning drive customer-facing outcomes. This is a hands-on architecture role embedded in an established delivery team. You’ll own solution designs … Machines through standards, reusable patterns, and ways of working The Team You’ll join a high-performing, multi-disciplinary team delivering a large-scale machine learning platform for a global telecommunications client. The team operates with high autonomy and shared ownership, and works in a hybrid setup with ...

capability from the ground up, in an organisation where the work genuinely matters. The roleThis is a hands-on leadership role combining statistical analysis, machine learning and business acumen to identify opportunities, solve complex problems and drive measurable value, not for its own sake, but to strengthen … large, complex datasets to identify trends, patterns and opportunities for improvement Develop, test and deploy predictive and statistical models as data maturity increases Apply machine learning techniques and emerging AI developments to real-world problems Collaborate closely with a data engineer to ensure data availability and quality Communicate ...

DescriptionCertificationsNVIDIA certifications (NCP-AI Infrastructure, or NVIDIA Deep Learning Institute credentials) — strongly preferred. Cloud AI/ML certification: AWS Certified Machine Learning – Specialty, Microsoft Certified: Azure AI Engineer Associate, or Google Professional Machine Learning Engineer — at least one preferred. Kubernetes: CKA or CKAD — preferred. TOGAF … degree in Computer Science, Computer Engineering, or a related technical field, or equivalent demonstrable experience. Advanced degree (MS in CS/AI/ML or related) beneficial but not required given sufficient hands-on depth. Continuous, demonstrable learning in AI — publications, open-source contributions, conference speaking, or lab-based ...

retail brand that is investing heavily in customer data, personalisation, and AI to transform how it engages with millions of customers. Data and machine learning are at the heart of their strategy, driving more relevant customer experiences, personalised marketing, and customer-centric decision-making across the business. They … Opportunity As the Data Science Manager, you'll lead both the technical direction and development of the team, helping shape the roadmap for how machine learning and advanced analytics are used to better understand customers and deliver personalised experiences at scale. You will be responsible for translating complex ...

160+ countries. Cutting edge tech: You'll be developing state of the art systems to prevent and detect crime in real time, spanning machine learning, LLMs and anything else your team feels is needed to tackle the problem. Product led company: Wise lives and breathes empowerment. Our growth … This is where you come in. Our vision is clean money without borders. We have made great progress in developing a general crime catching machine learning model, and now we need to dig deeper, and get a whole lot more specific. You'll dive deep into criminal typologies ...

simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days. Ki is proudly the biggest global algorithmic insurance carrier. … Understanding of infrastructure as code using tools such as Terraform. Data & Algorithms: Intermediate understanding of the control, management, and lifecycle of data products and machine learning algorithms. Industry Knowledge & Compliance: Understanding of the importance of market compliance and core regulatory requirements within the insurance space. Communication Skills: Highly ...

achieve? The goal: Build a high-performing software engineering organisation that reliably delivers customer value while providing the platform and infrastructure that enables our machine learning and research teams to succeed. Outcome – an elite engineering team. We've built solid foundations: continuous deployment, modern observability, high test coverage … ambitious objectives, and a high bar for performance. We need make measurable progress through tangible, realistic goals. You'll partner with the Head of Machine Learning, Head of Product, and the CTO to turn company priorities into realistic engineering plans. You'll help teams make thoughtful trade-offs ...

Enterprise Architect — Artificial Intelligence AI/ML Infrastructure, Platform & Governance Role Summary World Wide Technology is looking for a deeply technical Enterprise Architect who will own the delivery of AI projects end to end from the silicon and data center design that underpins AI workloads, through the software and MLOps … while mentoring delivery teams and shaping WWT's broader AI point of view. Key Responsibilities Own end-to-end technical delivery of AI/ML engagements: architecture definition, design authority, build oversight, and go-live validation. Host and chair Architecture Review Board (ARB) and Technical Design Authority (TDA) sessions ...

experiments, and translating findings into concrete deliverables. Our focus areas are: LLM Training (Continued Pretraining, Instruction Tuning, Reinforcement Learning Alignment, Distributed Training, Efficient ML techniques) Post-training techniques for planning, reasoning & complex workflows (e.g., Reasoning Models, LLMs + Knowledge Graphs, Test time compute, CoT pipelines, Tool use & API calling … Research Scientist Manager, you will play a key part in leading a diverse global team of experts. We hire world-leading specialists in ML/NLP/GenAI, as well as Engineering, to drive the company’s leading internal AI model development. You will have the opportunity to publish your ...

Dina Hussain Location: London, United Kingdom - Hybrid Skills: Data Science, Machine Learning, AI, LLM, GenAI As a Senior Specialist Solutions Engineer (SSE), ML Engineering, you will be the trusted technical ML expert to both Databricks customers and the Field Engineering organisation. You will work with Solution Architects … guide customers in architecting production-grade ML applications on Databricks, while aligning their technical roadmap with the evolving Databricks Data Intelligence Platform. You will continue to strengthen your technical skills through applying the latest technologies in GenAI, LLMOps, and ML, while expanding your impact through mentorship and establishing yourself ...

measurable business value from AI investments. MINIMUM (ESSENTIAL) REQUIREMENTS: Proven track record of accountability for the delivery of complex, production-grade AI/ML solutions at scale. Demonstrable experience of technical leadership in AI delivery. Deep expertise in developing and assuring advanced AI/ML models, including time series, supervised … DESIRABLE: Experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), and advanced ML libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Active contribution to open-source ...

measurable business value from AI investments. M INIMUM ( ESSENTIAL ) REQUIREMENTS : Proven track record of accountability for the delivery of complex, production-grade AI/ML solutions at scale. Demonstrable experience of technical leadership in AI delivery. Deep expertise in developing and assuring advanced AI/ML models, including time series … ESIRABLE : Experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), and advanced ML libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Active contribution to open-source ...

measurable business value from AI investments. M INIMUM ( ESSENTIAL ) REQUIREMENTS : Proven track record of accountability for the delivery of complex, production-grade AI/ML solutions at scale. Demonstrable experience of technical leadership in AI delivery. Deep expertise in developing and assuring advanced AI/ML models, including time series … ESIRABLE : Experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), and advanced ML libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Active contribution to open-source ...

About the role The AI & ML Engineering team accelerates the adoption of AI across the business, championing innovation while ensuring our machine learning solutions are robust, scalable, and cost-efficient. We enable teams to solve problems using existing AI tools where possible and build custom solutions when needed. … remit spans AI enablement, agentic systems development, and “conventional” ML engineering for non-GenAI applications e.g. recommender systems, forecasting models, and more. We’re looking for an AI & ML Engineer who is passionate about building production‐ready AI and machine learning solutions. You'll work across a variety ...

lifecycle of AI product engineering—from architectural design and prototyping to CI/CD-enabled deployment—using modern platforms and tools such as Azure ML, Databricks, MLflow, LangChain and LangGraph. Champion automation, testing, and observability across pipelines.· Operational Excellence: Define reusable development patterns, enforce coding standards, and promote MLOps best … processing and other relevant AI fields.· Proven track record of designing, developing, and deploying AI systems in production environments.· Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers).· Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks ...

Evaluation Frameworks and Benchmarks for long-horizon prediction, scene fidelity, and driving performanceWhat You'll BringMust-haves:3+ years of experience developing and deploying ML systems in real-world or production settingsPhD, Master's degree, or equivalent experience in Machine Learning, Computer Vision, Robotics, or a related fieldDeep … simulation systemsFamiliarity with large-scale training (e.g., FSDP, DeepSpeed, JAX)Experience with sim-to-real transfer or data-efficient learningContributions to open-source ML tools or research infrastructureWhat we offer you Attractive compensation with salary and equity Immersion in a team of world-class researchers, engineers and entrepreneurs A unique ...

clean, efficient, and scalable code that adheres to software engineering principles, MLOps practices, and cloud-native development. AI Solution Delivery: Own the implementation of ML pipelines, APIs, and data integration workflows. Operational Excellence: Contribute to defining reusable development patterns, enforcing coding standards, and implementing MLOps best practices that support version … processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks ...

agent ecosystems encompassing multi-agent orchestration, tool use, skills use, and memory systems, as well as foundation model integration, fine-tuning strategies, and classical ML model deployment within cohesive, production-ready platforms. You will be accountable for ensuring the complete architecture meets the most rigorous non-functional requirements across security … strategy — adaptation, fine-tuning, and dynamic cost/quality/latency-aware routing Set the standards for high-throughput, low-latency inferencing and classical ML deployment within unified, production-ready platforms Own the architecture of the enterprise context layer — knowledge graphs, ontologies, vector search, and semantic retrieval — grounding the solution ...

coaching, and exposure that will accelerate your growth in ways you won't find anywhere else. When you join us, you will have: Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear … actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey. A voice that matters: From day one, we value your ideas and contributions. You'll make a tangible impact ...

Senior Computer Vision Engineer - Deep Learning Salary: £70,000 to £95,000 Location: West London Working arrangement: Predominantly office and customer-site based, with some remote working available Employment: Permanent, full-time. Contract opportunities may also be considered. MFK Recruitment is recruiting a Senior Computer Vision Engineer … innovative UK technology company working at the forefront of computer vision, perception and autonomy. The company develops advanced Artificial Intelligence and Machine Learning technology for defence, security and other demanding real-world environments. Its work combines machine vision, deep learning and neuroscience-inspired approaches to create ...

intelligence layer: models, reasoning mechanisms, and evaluation approaches that turn data into insight and foresight. Key Responsibilities Design and train ML models where learning adds clear value Combine ML with: Statistical models Rule-based or symbolic components Develop models that operate over time (longitudinal, adaptive) Explore early agentic … outputs into human decision-making workflows Who You Are Strong background in machine learning or applied AI Comfortable working across paradigms (ML, causal, symbolic) Interested in how intelligence behaves in real systems, not just benchmarks Thoughtful about misuse, bias, and overreach Excited by building AI systems that remain ...

integrity, innovation and a willingness to challenge consensus. The Machine Learning Researcher will have a deep understanding of the principles behind modern ML algorithms — including recent advances such as transformer-based architectures and other state-of-the-art frameworks — and the ability to turn that knowledge into high … impact, production-ready solutions. The role involves applying advanced ML techniques to a wide range of forecasting challenges, building scalable ML pipelines, and deploying them in production, while working with high-dimensional, noisy, structured and unstructured datasets. Experience applying ML models in financial markets is desirable, but exceptional candidates with ...

language understanding/processing, computer vision, LLMs, machine learning, algorithmic foundations of optimization, data mining, machine intelligence (Artificial Intelligence), AI/ML algorithms, deep learning or image processing, multimodal, multilingual and reinforcement learning. Experience with research from previous internships, full-time industry experience, personal projects … extend and improve on Google's product offering. Contribute to a wide variety of projects utilising natural language processing, artificial intelligence, data compression, machine learning, and search technologies. Please complete your application before 23rd October 2026. We encourage you to apply as early as possible as we review ...