226 to 250 of 2,185 Machine Learning Jobs in the UK

Data Scientists do this by listening to team members, understanding context and challenging business ideas. Data Scientists use diverse techniques - frequentist and Bayesian statistics, machine learning, exploratory and explanatory data analysis, causal inference, data visualization, monte carlo modelling, econometric analysis, etc. Such broad requirements call for the ability … analysis Run exploratory data analysis and turn it into questions which can be answered with analytical techniques Use simple analytics, statistical or causal inference, machine learning or any other techniques to answer questions and address problems Communicate results clearly and effectively Take care of unclear and ambiguous requirements ...

data at scale. Why this role stands out: Strategic ownership of cloud and data platforms across the business Direct involvement in enabling AI and machine learning at production scale Opportunity to modernise integration and developer tooling Strong influence over technical direction and platform investment Hybrid London working with … development through strong APIs and shared platform services Embedding automation, reliability and security into how systems are delivered and maintained Supporting the transition of machine learning from experimentation into real-world usage Growing and coaching engineers while raising overall engineering standards Acting as a senior technical partner ...

with an AI company in the trade and logistics space at a critical inflexion point, moving from enterprise pilots into production deployments. With strong ML capability already in place, they now need a senior contractor to come in and audit, structure, and productionise their existing ML systems . This role … building from scratch. The Role You will work directly with the technical co-founders to bring structure, scalability, and best practices across their ML and data setup, ensuring it is ready to support multiple enterprise deployments. Key responsibilities: * Audit current ML architecture, pipelines, and MLOps practices * Identify gaps in documentation ...

Description White Collar Factory (95009), United Kingdom, London, London Lead Data Scientist - Deep Learning Practitioner About this role Our Data Science team focuses on the development of Machine Learning and Deep Learning solutions, to solve business problems and deliver actionable insights. We are a talented, collaborative … insights from complex data, working in close collaboration with our business partners. This role will primarily focus on leading the development of proprietary deep learning models to address critical business challenges in underwriting. The role will also involve supporting our business partners as they develop advanced servicing products using ...

Description White Collar Factory (95009), United Kingdom, London, London Lead Data Scientist - Deep Learning Practitioner About this role Our Data Science team focuses on the development of Machine Learning and Deep Learning solutions, to solve business problems and deliver actionable insights. We are a talented, collaborative … insights from complex data, working in close collaboration with our business partners. This role will primarily focus on leading the development of proprietary deep learning models to address critical business challenges in underwriting. The role will also involve supporting our business partners as they develop advanced servicing products using ...

Consultant who combines deep technical capability with a strong consulting mindset. You’ll help clients unlock the value in their data, applying advanced AI, ML, and mathematical modelling techniques to drive measurable business outcomes. This role is ideal for someone who thrives in client-facing environments, enjoys shaping data science … trusted advisor to clients – helping them define their digital vision, identify opportunities, and translate data science into tangible value. Design and implement machine learning , deep learning , and large language model (LLM) solutions for real-world business challenges. Bring strong mathematical reasoning and estimation skills to build robust ...

Consultant who combines deep technical capability with a strong consulting mindset. You’ll help clients unlock the value in their data, applying advanced AI, ML, and mathematical modelling techniques to drive measurable business outcomes. This role is ideal for someone who thrives in client-facing environments, enjoys shaping data science … trusted advisor to clients – helping them define their digital vision, identify opportunities, and translate data science into tangible value. Design and implement machine learning , deep learning , and large language model (LLM) solutions for real-world business challenges. Bring strong mathematical reasoning and estimation skills to build robust ...

Machine Learning Engineering Manager We're building a new ML Engineering team and are looking for a strong technical lead to help take our machine learning capability from proof-of-concept to fully scaled, production-ready solutions. Sitting within our Group & Enterprise Services (GES) function, this … data scientists to deploy high-impact models reliably and at scale. You'll combine leadership, architectural thinking and deep engineering skills to shape the ML platform, coach engineers and deliver robust, enterprise-ready ML services. What you'll do * Lead, mentor and develop a small team of ML Engineers * Oversee ...

medium sized businesses. Operating in a highly data driven environment, they have built a profitable, automated lending platform supported by sophisticated statistical and machine learning models. The business is well capitalised, commercially mature, and continuing to invest heavily in data science as a core differentiator. The Role … with senior stakeholders across product, engineering, operations and commercial teams to ensure insights are embedded in decision making. Overseeing the use of probabilistic and machine learning models in production environments and contributing to longer term technical and modelling strategy. Helping the business prioritise where data science delivers ...

ML Engineer (Stealth AI Company) About the company We are building a foundational intelligence platform that transforms fragmented, proprietary information into durable institutional intelligence - enabling organisations to reason faster, preserve context, and compound knowledge over time. We are starting with information-dense, judgment-heavy industries where decision-making under uncertainty … organisational knowledge evolves We are intentionally not: a workflow automation tool a chat UI on top of documents a standalone "knowledge graph product" Graphs, ML, probabilistic reasoning, and human-in-the-loop systems are combined to solve a larger problem: How can organisations reason reliably over their own information ...

learning, graph neural networks, generative AI, and retrieval augmented system. Required Skills and Experience: 5+ years of professional experience delivering advanced AI/ML solutions in industry or engineering environments. Strong expertise in Python and AI/ML libraries: PyTorch, TensorFlow, Scikit‐Learn, Keras, NumPy, Pandas, JAX, XGBoost, PyTorch … Deep understanding of advanced modelling methods: deep learning, GNNs, computer vision, sensor fusion, vector embeddings, RAG, generative AI . Experience designing AI/ML architectures and providing strategic technical guidance to enterprise clients. Proficiency with cloud compute platforms for training and deployment (Azure, AWS, GCP, or similar). Strong ...

about building systems that generate real-time insights during live sport. Why This Role? Leading global streaming/sports platform Real ownership of ML systems at scale (millions of users) Solving complex real-time + low latency AI problems The Company/Product You’ll be working on a cutting … sport using AI to deliver personalised insights, predictions, and real-time data during live events. What You’ll Be Working On Leading development of ML systems for live sports insights + personalisation Building solutions across Computer Vision, ML, and Generative AI Turning live video + sports data into real-time ...

Senior Staff Machine Learning Engineer (Drug & Target Discovery) — Senior Technical Lead Ready to build the ML backbone behind next-generation human health discovery? We’re partnering on a retained search for a Senior Staff/Principal-level Machine Learning Engineer to lead the design, training … deployment of frontier ML systems across multi-omics, biomarker discovery, target discovery, genomics, and multimodal biomedical data. This is a rare opportunity to translate cutting-edge research into robust, production-grade systems that can improve how new treatments are discovered and developed. We’re looking for senior candidates with deep ...

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 ...

Lead ML Engineer - Onsite 5 days a week - London Happy to look at European relocators An Edtech Start-up in London are building something transformative in the education space using cutting-edge machine learning. We're looking for a Lead ML Engineer to take ownership of the machine learning strategy, build out the team, and help shape the future of AI in education. Responsibilities: Build and lead a new ML team from the ground up. Define the tech stack for data pipelines and ML models. Develop generative models using diverse datasets (text, audio, video, test results ...

production. This is a blended role combining MLOps, Data Engineering, and DevOps, well-suited to an engineer who enjoys working across the full ML and data lifecycle. You will work within dynamic, multi-disciplinary project teams, collaborating closely with data scientists, software engineers, and client stakeholders to deliver scalable, production … ready ML and data solutions across a diverse range of commercial sectors. This role offers strong opportunities for career development, exposure to real-world ML systems, and continuous learning within a fast-growing engineering team. Key Responsibilities & Skills: Own and manage the end-to-end lifecycle of machine ...

deliver real products used by investment teams and portfolio companies. This role is ideal for: PhD graduates in a STEM field with applied ML, optimization, or computational experience; or Bachelor’s/Master’s graduates with 1–2 years of industry experience or relevant internships in machine learning, data engineering, or software engineering. You’ll contribute to designing, implementing, and deploying production-grade ML systems—ranging from NLP pipelines to model‐driven workflow automation. You’ll learn quickly, gain real ownership, and see your work make tangible business impact. What You’ll Do Build and deliver ML ...

Lead high-impact data science initiatives end-to-end, including problem framing, methodology selection, experiment development, implementation partnership, and impact measurement.* Build and deliver machine learning and reinforcement learning solutions to improve player engagement, retention, monetization, and operational outcomes.* Lead the modeling framework for complex systems, guaranteeing … related quantitative field, or equivalent experience in practice.* Experience: 5+ years of professional data science experience. You have delivered at least 3 data or ML products from problem definition to production deployment and monitoring.* Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics.* Hands-on experience ...

Lead high-impact data science initiatives end-to-end, including problem framing, methodology selection, experiment development, implementation partnership, and impact measurement. Build and deliver machine learning and reinforcement learning solutions to improve player engagement, retention, monetization, and operational outcomes. Lead the modeling framework for complex systems, guaranteeing … related quantitative field, or equivalent experience in practice. Experience: 5+ years of professional data science experience. You have delivered at least 3 data or ML products from problem definition to production deployment and monitoring. Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics. Hands-on experience ...

hiring in Miami, London and Milan. Description -- Role: expected to contribute to production grade proprietary trading systems, deploy state of the art AI/ML, develop novel AI/ML models, experiment with and develop novel trading ideas, explore new datasets. -- Required: experience training ML models end to end (from … data processing to fine tuning), experience training across transformers/generative models/RL, publications in either top tier ML conferences (e.g., NeurIPS, ICLR, ICML, JMLR, etc.) or top scientific journals, top tier institutions/industry experiences. -- Positives but not requirement: PhD. Reference: AMC/AHU/NW/SPH001 ...

business challenges into actionable analytical and AI use cases, ensuring timely and high-quality execution. The data analyst will foster technical excellence and continuous learning in AI, machine learning, and advanced analytics. They will ensure adherence to governance standards, ethical AI practices, and robust model monitoring … analytics, automation, and AI-driven insights. Ensure ethical and responsible use of AI, including bias monitoring and compliance with data governance policies. Foster continuous learning and experimenting in AI, machine learning, and advanced analytics techniques. Monitor performance of AI models and analytics solutions; identify trends, anomalies ...

vehicle logs and simulation outputs to curated, labelled, and model-ready datasets. This includes handling multimodal sensor data, scaling labelling through both human and ML-based workflows, and enabling intelligent selection of high-value data from thousands of hours of real-world and simulated driving. This role sits close … into training-ready datasets Support hand-labelled and auto-labelled data pipelines, including validation and quality control Help build and scale autolabelling systems, where ML models generate annotations across large datasets Support intelligent data curation and selection from thousands of hours of real-world and simulated driving Generate and process ...

creator ecosystem, and developing models for strategic content valuation. Multi-objective balancing and long term measurement. We rely extensively on state-of-the-art ML around personalization, deep learning, causal inference, optimization, ranking and recommendation. What You’ll Do Within the Sharechat AI team, we are looking … engagement while minimizing server and cloud costs of serving large scale models, and act as a subject matter expert in the recommender systems and ML ranking domains. You would be joining us at an exciting time! The science behind recommendation systems is rapidly changing, and we’re making big progress ...

looking for a GCP Data Engineer to join a multidisciplinary team responsible for building and operating robust, cloud-native data infrastructure that supports ML workloads, particularly PyTorch-based pipelines. The Role You'll focus on designing, building, and maintaining scalable data pipelines and storage systems in Google Cloud, supporting ML … teams by enabling efficient data loading, dataset management, and cloud-based training workflows. You'll work closely with ML engineers and researchers, ensuring that large volumes of unstructured and structured data can be reliably accessed, processed, and consumed by PyTorch-based systems. Key Responsibilities Design and build cloud-native data ...

business outcomes. As a key partner for multi-functional teams, including game developers, data analysts, product, and game operations managers, you will use your ML and data expertise to build internal data tools. These tools will support decision making. You will also develop customer-facing data products that enable personalized … standard on data science benefit. Engineering Best Practices: Be responsible for the implementation of the best software engineering practices for internal tools and ML/RL model development, define software architecture standards, implement code review practices, auto-tests, improve observability, reproducibility and monitoring of ML/RL solutions. Infrastructure Ownership ...