1 to 25 of 184 Machine Learning Jobs in the City of London

both their technical platform and engineering capability. The Role They are hiring a Senior Machine Learning Engineer to take ownership of their ML strategy and help scale the company’s modelling and data capabilities. This role sits at the core of the business - bridging research, engineering, and product … applied across their discovery pipeline. You’ll be expected to lead from the front: setting technical direction, mentoring engineers, and building production-grade ML systems that integrate closely with biological research workflows. What You’ll Be Doing Lead the design and development of machine learning models applied ...

Machine Learning Engineer (MLOps Python LLM AWS) London/WFH to £90k Are you a senior Machine Learning Engineer looking for an opportunity to take ownership, working on complex and interesting systems? You could be progressing your career in a hands-on technical leadership role … product challenges. You'll define the Machine Learning roadmap from a technical perspective, evaluating model architectures, optimising data pipelines and ensuring that ML features provide actionable insights within the product. This isn't just about training models; it's about building the ML infrastructure that enables the business ...

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: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong 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 ...

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: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong 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 ...

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: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong 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 ...

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: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong 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 ...

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: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong 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 ...

with our hardware. Experience: Proven track record of developing novel algorithms (papers in NeurIPS, ICML, ICLR, CVPR, or Nature/Science journals) Hardware Aware ML/Neuromorphic Computing: FPGAs, ASICs, analog computing chips, spiking neural network (hardware), edge AI Unconventional training algorithms Reservoir computing, self-constrastive learning, forward-forward … learning, evolutionary algorithms, equilibrium propagation Physics informed neural networks, or applied ML to physics problems Deep understanding of mathematics, algebra/topology - key words are latent space, intrinsic dimensionality Experience working with hardware as well is a bonus ...

parts of the supply chain—enabling bulk inventory exchange, streamlined digital payments, and generating vast quantities of aggregated market data. By applying AI and machine learning techniques, we deliver predictive market insight and trading recommendations straight back to the trading environment—facilitating smarter everyday business decisions … align data strategy with broader business goals. You will play an integral role, taking ownership of a team focused on designing, developing, and deploying ML systems to solve real world problems and enhance business processes, leveraging cloud platforms to build, train, and scale ML models. As Head of Data Science ...

fast and accurate results • Designing and implementing agentic AI workflows powered by LLMs • Building and maintaining scalable data pipelines • Leading technical decision-making across ML and NLP projects Requirements • 8+ years of commercial engineering and/or data science experience • Experience in technical leadership or leading ML initiatives • Strong Python … programming skills • Commercial experience with machine learning • Experience working in Natural Language Processing (NLP) • Experience training ML models using TensorFlow and/or PyTorch • Experience with search databases (e.g. Elasticsearch, OpenSearch) • Experience with cloud platforms (e.g. AWS) • Willingness to work 3 days per week onsite in London Benefits ...

available £45k to £95k DoE plus 15% clearance bonus Must be willing to be full-time on-site in Central London Skills required in machine learning, GenAI, NLP, Customer Engagement/Consultancy Who are we? We are recruiting Junior, Senior and Lead Data Scientists with AI specialism … look forward to hearing from you. KEY SKILLS: Data Science/Data Scientist/AI Engineer/AI/Machine Learning/ML/NLP/GenAI/Stakeholder Engagement/Customer Engagement/AWS/Azure/Cloud/Docker/Kubernetes/CI/CD/ ...

Principal Machine Learning Engineer to play a key role in shaping the architecture, strategy, and delivery of large-scale production ML systems powering live sports environments. This is a genuinely high-impact opportunity for someone who enjoys solving complex real-time engineering challenges while influencing technical direction across … platform teams. Key areas of focus include: Real-time sports insights & personalisation Computer vision & multimodal AI Live event detection & metadata generation Low-latency ML inference systems End-to-end MLOps & production ML Scalable cloud-native AI platforms What they’re looking for: Strong experience leading ML engineering initiatives in sports ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

engineering environment. Required: Core experience Strong grounding in audio machine learning or applied signal processing Experience training and evaluating models using modern ML tooling Awareness of real-world acoustic challenges such as noise, reverberation, and variability Comfort working in a small, fast-moving engineering team Likely … + some industry experience Beneficial Edge or embedded ML optimisation Audio feature extraction or DSP knowledge Postgraduate study in a relevant technical discipline Experience with sensing, monitoring, or real-world data systems ...

defence environments. This is an opportunity to work at the cutting edge of data science, focusing on GenAI, large language models, and cloud-based ML deployments, while also taking on leadership responsibilities within a growing team. Role Responsibilities Lead day-to-day technical delivery across data science and ML projects … data governance and security best practices Desirable Skills Experience using GPUs in cloud environments Knowledge of MLOps, CI/CD pipelines, and monitoring ML models Experience building APIs and working with modern DevOps practices Eligibility Requirements Due to the nature of the work, candidates must: Hold active DV clearance ...

, optimisation and operational research techniques Strong Python expertise with experience delivering production‐quality data science software Experience working with cloud platforms and modern ML tooling Strong software engineering discipline including testing, CI/CD and version control Ability to structure complex business and technical problems and propose pragmatic solutions … resilience and adaptability in fast‐moving environments Strong commitment to delivering measurable business value Your experience: Master’s degree or greater in data science, ML, or operational research, or 6+ years of highly relevant industry experience (required) 4-6 years working on production ML or optimization software products at scale ...

Lead Machine Learning Engineer £Up to £125000 GBP Hybrid WORKING Location: Central London, Greater London - United Kingdom Type: Permanent Reference: AMC/ERO/Lead Machine Learning Engineer Postcode: SW1 JBG81_UKTJ click apply for full job details ...

predictive insights during the action. As a Principal Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. For this role we offer … approach with 2 days a week onsite in Osterley office . What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture ...

predictive insights during the action. As a Principal Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. For this role we offer … approach with 2 days a week onsite in Osterley office . What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture ...

predictive insights during the action. As a Principal Machine Learning Engineer , you'll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans. For this role we offer … approach with 2 days a week onsite in Osterley office . What you'll do: You'll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation , real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture ...

Machine Learning Engineer (MLOps Python LLM AWS) London/WFH to £90k Are you a senior Machine Learning Engineer looking for an opportunity to take ownership, working on complex and interesting systems? You could be progressing your career in a hands-on technical leadership role ...

will focus on continuously maturing the platform to support report integrations, as well as advanced capabilities in artificial intelligence (AI), machine learning (ML), and analytics. As a key member of the data team, you will focus on: Strategically designing the data platform, including the evolution of data domains … data lifecycles across Gallagher Re processes in line with supporting technical architecture. Analytics Sandboxes : Enable secure, flexible environments for data experimentation and innovation. AI & ML Opportunities : Facilitate the adoption of AI and machine learning solutions. Client Preferences : Implement data structures and automated processes to capture, manage, and utilise ...

developers and researchers. 🛠️ Skills and Experience 5+ years of experience in software engineering, with a strong focus on AI and Machine Learning (ML). Expert-level proficiency in Python and deep learning frameworks, particularly PyTorch. Proven experience building and deploying applications with LLM APIs such as OpenAI … MacBook and Apple Display provided. Team: Become part of a supportive and passionate team environment. If you are driven to redefine the capabilities of machine learning and eager to make a significant impact, Ultralytics offers an exceptional career opportunity. ...

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. ...

clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity … needs of GS engineers. Be part of our continual drive to innovate and uplift our platforms to take advantage of new technologies (such as machine learning, cloud platforms) Provide technical guidance and support to other team members and stakeholders. Stay up to date with the latest industry trends ...