1 to 25 of 388 Permanent Machine Learning Jobs in London

Machine Learning Engineer Join the analytics team as a Machine Learning Engineer in the insurance industry, where you'll design and implement innovative machine learning solutions. This permanent role in London offers an exciting opportunity to work on impactful projects in a forward-thinking environment. Client Details Machine Learning Engineer This opportunity … is with a medium-sized organisation in the insurance industry. The company is committed to utilising advanced analytics and machine learning to enhance its services and deliver value to its clients. Description Machine Learning Engineer Design and develop machine learning models to address key business challenges in the insurance sector. Collaborate with the analytics … team to identify opportunities for leveraging data-driven solutions. Deploy machine learning algorithms into production environments efficiently. Optimise model performance and ensure scalability for large data sets. Analyse and interpret data to provide actionable insights for stakeholders. Stay updated with the latest advancements in machine learning and data science technologies. Document processes and create clear, concise More ❯

Machine Learning Engineer Join the analytics team as a Machine Learning Engineer in the insurance industry, where you'll design and implement innovative machine learning solutions. This permanent role in London offers an exciting opportunity to work on impactful projects in a forward-thinking environment. Client Details Machine Learning Engineer This opportunity … is with a medium-sized organisation in the insurance industry. The company is committed to utilising advanced analytics and machine learning to enhance its services and deliver value to its clients. Description Machine Learning Engineer Design and develop machine learning models to address key business challenges in the insurance sector. Collaborate with the analytics … team to identify opportunities for leveraging data-driven solutions. Deploy machine learning algorithms into production environments efficiently. Optimise model performance and ensure scalability for large data sets. Analyse and interpret data to provide actionable insights for stakeholders. Stay updated with the latest advancements in machine learning and data science technologies. Document processes and create clear, concise More ❯

Description The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm's data and analytics journey. As a part of CDAO, The Machine Learning Center of Excellence (MLCOE) partners across the firm to shape, create, and deploy Machine Learning Solutions for our most challenging business problems. This includes ensuring the quality … to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm's commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly. As a Summer Associate within the MLCOE, you will apply sophisticated machine … and more. Your project will have direct impact on JPMorgan's businesses, will be integrated into our product pipelines, or be part of published research in top AI/ML conferences. Full-time employment offers may be extended upon successful completion of the program within our hybrid work model. Job responsibilities Research and explore new machine learning methods More ❯

Machine Learning Operations Engineer Our financial services client based in London is looking to recruit a Machine Learning Operations Engineer ASAP. The position will be a Hybrid role be working from home and their offices in London. To be considered for the role you must have the following essential skills & experience: Key Skills & Experience Model development … Work collaboratively with actuarial analysts to develop machine learning and statistical models to predict outcomes, related to pension schemes, such as life expectancy, default risk, or investment returns. Identify appropriate machine learning algorithms and apply them to enhance predictions, automate decision-making processes, and improve client offerings. Machine Learning Operations: Responsible for designing, deploying … team and non-technical stakeholders within the company. Technical Skills required Previous experience in designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity with data visualization and reporting More ❯

Machine Learning Operations Engineer Our financial services client based in London is looking to recruit a Machine Learning Operations Engineer ASAP. The position will be a Hybrid role be working from home and their offices in London. To be considered for the role you must have the following essential skills & experience: Key Skills & Experience Model development … Work collaboratively with actuarial analysts to develop machine learning and statistical models to predict outcomes, related to pension schemes, such as life expectancy, default risk, or investment returns. Identify appropriate machine learning algorithms and apply them to enhance predictions, automate decision-making processes, and improve client offerings. Machine Learning Operations: Responsible for designing, deploying … team and non-technical stakeholders within the company. Technical Skills required Previous experience in designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity with data visualization and reporting More ❯

the products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Lead Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data … Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy … bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high More ❯

hours and opportunities to contribute to frontier AI evaluation and research. Key Responsibilities Evaluate and compare AI-generated research plans for clarity, feasibility, and technical soundness. Design and compile ML tasks based on real-world challenges and research competitions. Draft detailed, executable natural language plans for machine learning workflows. Implement and validate research plans in Python within a … concise, objective feedback. Ideal Qualifications 5+ years of experience in applied machine learning or a PhD in machine learning or related fields. Strong understanding of ML research methodologies, experimental design, and evaluation practices. Excellent analytical and technical writing skills. Experience with reproducibility or benchmarking in ML research preferred. Detail-oriented and able to deliver high-quality …/hour Payment: Weekly via Stripe Connect Contract Type: Independent contractor engagement Structure: Remote, milestone-based evaluation with flexible scheduling Application Process Submit your resume or CV highlighting relevant ML research or engineering experience. Complete a short AI-based interview and a brief questionnaire about your experience with reproducibility and model benchmarking. Selected candidates will receive detailed onboarding materials and More ❯

this role, you won't just analyse data; you'll answer the critical questions that drive our strategy. We're looking for someone to use advanced data science and machine learning to uncover the 'why' behind customer behaviour, such as identifying complex churn triggers for our energy customers. You will also develop and own the models that quantify … Lifetime Value (LTV) and Customer Acquisition Cost (CAC). This isn't a research role. We need a "full-stack" data scientist who can own the end-to-end ML lifecycle. You will take your ideas from initial Proof of Concept (POC) and exploratory analysis all the way through to building, deploying, and maintaining production-ready models, collaborating closely with … our Machine Learning Engineers. We work together. Your team and the people you will work with... Our Data teams are small, empowered, and cross-functional, taking full ownership of the solutions they build. We adopt the technologies that best support our goals and continuously raise the bar on how we deliver value. UW’s Data team is a More ❯

at the heart of an established data function, working on real production workloads rather than prototypes. You'll play a key role in shaping how intelligent automation, LLMs and ML-driven services are designed, deployed and continuously improved. What you'll be working on * Designing and delivering Gen AI and LLM-driven applications* Building and maintaining machine learning pipelines and data workflows* Developing cloud-native (serverless) ML components within a distributed engineering team* Improving existing ML systems and identifying opportunities for optimisation* Supporting sprint planning, estimation and shaping a healthy product backlog What you'll need to bring * Strong hands-on Python skills and solid grounding in algorithms and software engineering* Experience designing ML/AI solutions … and working with common architecture patterns* Background in serverless data/ML pipelines (Azure preferred, AWS/GCP welcome)* Proficiency in SQL and NoSQL data stores* Broad understanding of machine learning methods (regression, tree-based models, clustering, deep learning, attention models, transformers, vector representations)* Ability to explain technical concepts clearly to a range of stakeholders* Confidence estimating More ❯

Instructor to support delivery across the Machine Learning Engineer (Level 6) Apprenticeship and wider commercial programmes. If you're a passionate technologist who loves bringing complex ML concepts to life — from maths foundations to real-world deployment — this is your chance to make a real impact. What you'll do You'll play a key role in … helping learners and professionals build deep, practical ML capability. Day-to-day, you'll: ? Deliver engaging teaching sessions covering the full ML lifecycle — data prep, model training, evaluation, deployment and monitoring at scale. ? Explain the maths behind ML models (linear algebra, calculus, probability, stats) in an accessible, engaging way. ? Support learners throughout their apprenticeship journey alongside Learner Success Coaches. ? Contribute … delivery meets the standards expected by Ofsted, ESFA and other awarding bodies. What we're looking for You'll need to bring: Strong industry experience in end-to-end ML projects — from data wrangling and model building to deployment and monitoring. Confident teaching ability — whether you've formally taught, mentored or coached technical teams. Mathematical depth — clear understanding of the More ❯

Snapshot Science is at the heart of everything we do at Google DeepMind. We are committed to using AI and machine learning to accelerate scientific discovery and tackle some of humanity's biggest challenges. The development of fault-tolerant quantum computing represents one of the most profound scientific and computational challenges of our era. In the Science team … progress in this field. This is an opportunity to conduct groundbreaking research at the intersection of quantum computing and artificial intelligence. Our team is focused on leveraging cutting-edge machine learning to push the boundaries of what's possible in quantum simulation and algorithm development. You will join a multidisciplinary team of world-class researchers and engineers to … ideas, run experiments, and publish your findings, with the goal of advancing quantum science through the application of artificial intelligence. Key responsibilities: Design and execute research projects, applying modern ML techniques (including generative AI) at the intersection of quantum computing and machine learning. Identify, develop and test classical and quantum algorithms with a focus on real-world quantum hardware. More ❯

the beginning of our journey - and we are very excited about our plans for growth over the coming year and beyond The role We are now looking for a Machine Learning Research Engineer to help build and deliver a platform that can automatically create Virtual Agents for operational processes currently undertaken manually using browser-based UIs. An important … our customer-facing technical teams Utilise best-in-class capabilities to deliver these capabilities Research, invent and create novel capabilities where gaps in industry require it Participate in our machine learning community to influence how we implement machine learning and computer vision technologies, shaping Unitary's future. Contribute full-stack development, including software engineering, DevOps, and … are happy to get stuck into whatever needs doing, and are ready to learn and grow with the company. For this particular role, we need a proactive AI and machine learning expert who is familiar with leveraging and creating AI capabilities and who is comfortable engaging with customers and exploring and presenting new ideas. Strong communication skills are More ❯

for integrations, asyncio for concurrent processing, and building robust automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep expertise in AI/ML frameworks including TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model … SQL Server), data validation, cleansing workflows, scheduling tools (Azure Data Factory), and ensuring data quality for machine learning applications. Machine Learning Operations (MLOps) - Experience deploying ML models to production environments using containerisation (Docker), orchestration (Kubernetes), model versioning (MLflow, DVC), monitoring model performance and drift, A/B testing frameworks, and implementing CI/CD pipelines for … model training and deployment. Understanding of model governance, explainability, and compliance requirements. Solution Architecture & Technical Design - Ability to design end-to-end automation architectures that combine multiple technologies (BPA, ML, GenAI, APIs) into cohesive solutions. Experience creating technical design documents, system architecture diagrams, assessing build vs. buy decisions, estimating effort and complexity, and presenting technical recommendations to both technical and More ❯

The Role Reporting to the Machine Learning Lead, youll be a hands-on Machine Learning Engineer with a strong track record of building and deploying ML solutions at scaleparticularly in NLP and GenAI. You will: Design, develop and scale NLP and GenAI capabilities to optimise business processes. Build out a robust GenAI application technology stack, from … experimentation through to production. Develop, maintain and improve existing ML pipelines, data transformation workflows and MLOps practices. Create serverless data/ML pipelines in cloud environments (Azure preferred). Work closely with architects, senior developers, product owners and business analysts to shape requirements, solution design and architecture. Own user stories end-to-end, contribute to sprint planning, and provide accurate … estimates for delivery. Translate business problems into well-structured ML and automation solutions using data-led insight. Collaborate with wider technology teams to share knowledge, improve processes, and produce training/documentation. The Person Were looking for someone who combines strong engineering fundamentals with practical ML delivery experience, and who enjoys working collaboratively in agile teams. Youll bring: Strong Python More ❯

in office) Up to £120,000 Shares + Benefits A fast-growing Data & AI Product-based company at the forefront of cutting-edge AI solutions are looking for an ML Lead to join the team and spearhead a number of ambitious products, shaping the architecture, direction, and delivery of advanced AI and Machine Learning initiatives. What youll do … Lead the design and development of Agentic AI systems, generative models, and NLP-powered solutions. Guide and manage a small talented ML engineering team, fostering innovation and technical excellence. Collaborate with product, data science, and engineering teams to bring state-of-the-art research into production. Evaluate and implement the latest AI frameworks, libraries, and cloud tools. Champion best practices … in model deployment, evaluation, and optimisation. What were looking for Strong track record in ML leadership, ideally in production-scale AI systems. Expertise in Agentic AI, LLM-based architectures, NLP techniques, and generative AI models. Solid programming skills (Python preferred) and experience with ML frameworks such as PyTorch, TensorFlow, Hugging Face. Hands-on experience with prompt engineering, fine-tuning LLMs More ❯

hours Based in Central London Over the course of 10 weeks, G-Research Summer Research Programme interns gain a unique insight into life as a Machine Learning (ML) practitioner at a leading quantitative finance research firm. Our full-time ML researchers use a wide range of tools and techniques in an applied setting, putting their expertise to use … in direct, production-ready applications with immediate results. They have access to vast computing resources and are limited only by their imagination. As an ML intern, you will have the opportunity to experience some of this as part of a 10-week programme working on a meaningful and challenging research project that demands the application of innovative yet pragmatic mathematical … opportunities on completion of their studies. Who are we looking for? The ideal candidate will, at a minimum, have experience in the following areas: A post-graduate degree in Machine Learning or a related discipline, or commercial experience developing novel machine learning algorithms. We will also consider exceptional candidates with a proven record of success in More ❯

contributing to scalable software architecture and defining best practices. Working with clients, and cross-functional teams, you'll ensure technical feasibility and timely delivery of high-quality, production-grade ML systems. What you'll be doing: Building and deploying production-grade ML software, tools, and infrastructure. Creating reusable, scalable solutions that accelerate the delivery of ML systems. Collaborating with engineers … project feasibility and impact. Defining and implementing Faculty's standards for deploying machine learning at scale. Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders. Who we're looking for: You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or … GCP), including architecture and security. You've worked with container and orchestration tools such at Docker & Kubernetes to build and manage applications at scale You are comfortable with core ML concepts, including probability, statistics, and common learning techniques. You're an excellent communicator, able to guide technical teams and confidently advise non-technical stakeholders. You thrive in a fast More ❯

your CV/data private, feel free to WhatsApp your details/CV to me, Dan - WHO WE ARE: We're a rapidly growing AI-powered technology startup combining machine learning and automation to drive innovation across the healthcare. Our mission is to use advanced AI systems to streamline operations, enhance insights, and improve real-world wellbeing outcomes. … Lead and deliver AI and machine learning projects in collaboration with cross-functional teams (engineering, product, and domain experts). Design, develop, and deploy end-to-end ML systems , from concept to production. Build models for intelligent automation, natural language processing (NLP), and data-driven insights. Work with Python , PyTorch , TensorFlow , and scikit-learn to prototype and scale … and reliability in real-world environments. AI SCIENTIST - ESSENTIAL SKILLS: Proven experience designing, training, and deploying machine learning models in production. Strong proficiency in Python and key ML frameworks ( PyTorch , TensorFlow , scikit-learn ). Deep understanding of machine learning algorithms and statistical modelling. Ability to work independently while collaborating effectively within technical teams. Excellent analytical , problem More ❯

/data private, feel free to WhatsApp your details/CV to me, Dan - 07704 152638 WHO WE ARE: We're a rapidly growing AI-powered technology startup combining machine learning and automation to drive innovation across the healthcare. Our mission is to use advanced AI systems to streamline operations, enhance insights, and improve real-world wellbeing outcomes. … Lead and deliver AI and machine learning projects in collaboration with cross-functional teams (engineering, product, and domain experts). Design, develop, and deploy end-to-end ML systems , from concept to production. Build models for intelligent automation, natural language processing (NLP), and data-driven insights. Work with Python , PyTorch , TensorFlow , and scikit-learn to prototype and scale … and reliability in real-world environments. AI SCIENTIST - ESSENTIAL SKILLS: Proven experience designing, training, and deploying machine learning models in production. Strong proficiency in Python and key ML frameworks ( PyTorch , TensorFlow , scikit-learn ). Deep understanding of machine learning algorithms and statistical modelling. Ability to work independently while collaborating effectively within technical teams. Excellent analytical , problem More ❯

to influence not just their engineering roadmap, but how they fundamentally approach solving complex, real-world security challenges with data. You'll work at the intersection of data science, ML infrastructure, and product innovation, leading efforts to build and evolve ML-driven capabilities, while also ensuring the reliability and scalability of their models in production environments. What You'll Do … learning models focused on understanding behaviour patterns and identifying cybersecurity anomalies. Partner with product, engineering, and domain experts to translate strategic goals and customer needs into practical, scalable ML solutions. Drive model development end-to-end, from exploratory analysis, feature design, and prototyping to validation and deployment. Collaborate with platform and infra teams to operationalize models and ship ML … powered features into production. Continuously assess and iterate on production models, balancing long-term ML strategy with tactical improvements. Champion code quality, observability, and resilience within their ML systems through reviews and hands-on contributions. Help shape their internal ML standards and practices, ensuring they stay ahead of industry advancements. Offer technical mentorship and be a thought partner to colleagues More ❯

to influence not just their engineering roadmap, but how they fundamentally approach solving complex, real-world security challenges with data. You'll work at the intersection of data science, ML infrastructure, and product innovation, leading efforts to build and evolve ML-driven capabilities, while also ensuring the reliability and scalability of their models in production environments. What You'll Do … learning models focused on understanding behaviour patterns and identifying cybersecurity anomalies. Partner with product, engineering, and domain experts to translate strategic goals and customer needs into practical, scalable ML solutions. Drive model development end-to-end, from exploratory analysis, feature design, and prototyping to validation and deployment. Collaborate with platform and infra teams to operationalize models and ship ML … powered features into production. Continuously assess and iterate on production models, balancing long-term ML strategy with tactical improvements. Champion code quality, observability, and resilience within their ML systems through reviews and hands-on contributions. Help shape their internal ML standards and practices, ensuring they stay ahead of industry advancements. Offer technical mentorship and be a thought partner to colleagues More ❯

solve the hardest problems. ‍Accountability for every result. ‍Integrity always. About The Role The purpose of this role is to advance clients' technical environments by designing and deploying innovative machine learning-based models and AI solutions that directly deliver measurable value for their organizations. This role is designed for impact, and we believe our best work happens when … of machine learning algorithms for supervised and unsupervised learning Understanding of Transformer based models Experience developing AI agents Strong Python and SQL skills Experience with Cloud ML tools and version control (e.g. git) Experience with MLOps Collaborative, proactive, logical, methodical, and attentive to detail Excellent communication skills (verbal and written) Collaborate with clients to understand their business … problems and design technical solutions using machine learning models Develop and deploy machine learning models on Google Cloud Use version control and agile working practices Stay up-to-date with the latest developments in machine learning and bring new ideas to the team. Requirements What Success Looks Like Demonstrates adeptness in persuasive communication and More ❯

Data Scientist & Machine Learning Engineer - Fully Remote We are currently working on a fully remote, data-driven gaming & entertainment company that's scaling its Data Science and Machine Learning capabilities across Europe. The business has around 100 employees globally and is deeply invested in analytics, experimentation, and automated decision-making.They're now hiring for: Senior Data … and frequent interaction with C-level stakeholders, so strong communication and statistical depth are essential.Tech: Python, SQL, GCP. Machine Learning Engineer Focused on deploying, maintaining, and monitoring ML systems. You won't be building models but will work closely with DS and engineering teams to ensure performance and reliability. Quality and resilience matter more than years of experience.What More ❯

people love. And we do it all right here at Sky. As a Machine Learning Engineer you will be responsible for the improvements and maintenance of our ML Framework, supporting a team of Data Scientists to deploy a variety of Machine Learning and AI models into production. The role works closely in collaboration with Data Scientists … Self-starter who can work independently to deliver improvements to the framework. Forward looking, always seeking for new ways to improve and develop on existing processes. Work closely with ML Engineers from other teams to share learnings and accelerate development of new features What you'll bring Advanced working knowledge of Vertex AI and the wider GCP ecosystem. Great communication … skills to aid the Principal Data Scientist to develop long term roadmaps and be comfortable presenting to Data leaders when needed. Strong working knowledge of modern ML frameworks (e.g., XGBoost, Scikit-learn, TensorFlow) and experience applying them to real-world problems. Proficiency in writing clean, maintainable, and efficient code in Python and SQL. Solid understanding of software engineering principles, including More ❯

LLMs) and generative AI. In this pivotal role, you will be responsible for developing and implementing a forward-looking IAM program tailored to the complexities of CDAO & AI/ML data platforms. You will anticipate emerging threats, challenge the status quo, and apply your expert judgment to solve real-world challenges that impact our company, our customers, and our communities. … artificial intelligence, we invite you to join our dynamic team. Job Responsibilities: Pioneer a Visionary IAM Strategy: Develop and execute a comprehensive IAM roadmap for our CDAO & AI/ML data platforms, incorporating the latest advancements in securing LLMs, machine learning models, and the entire AI development lifecycle. Secure the AI Ecosystem: Engineer robust access control mechanisms for … large-scale datasets, model training and inference environments, and the AI/ML supply chain. This includes defining and managing identities for human users, AI models, and autonomous agents. Mitigate Emerging AI-Specific Risks: Conduct in-depth assessments of IAM technologies and processes to identify and address vulnerabilities inherent to AI systems, such as prompt injection, data poisoning, and model More ❯