51 to 75 of 426 Machine Learning Jobs in Central London

deploy machine learning systems that accelerate decision-making and unlock business value. You’ll design, implement and deploy production-grade AI and ML systems, ranging from NLP pipelines that extract insights from complex documents to integrating models with third-party services to streamline workflows. We’re looking … data-driven products that directly impact investment decisions and portfolio company performance. Drive measurable impact: Partner with internal desks and portfolio teams to integrate ML products into their existing workflows to drive high adoption and value. Move fast and iterate: Work in an agile environment where experimentation, pragmatic engineering ...

senior technical point of contact for AI, data science and statistical expertise across projects and bids Lead and contribute to complex AI/ML delivery alongside ML engineers, project managers and client stakeholders Scope and shape AI use-cases with customers, translating requirements into delivery roadmaps Build, test and deploy … machine learning models into cloud-based products and services Contribute to bid responses, including research into advanced AI/ML and statistical methods Present analytical findings and recommendations to internal teams and external customers Mentor and support junior data scientists and graduates Promote data science capability across ...

Language models that could be locally resident, problems in computer vision, speech, Natural Language Processing (NLP), multilingual models, applied statistics, data mining or conventional machine learning models. We look to our data scientists to be conversant with at least 2 or more of the above areas … conversant with deep learning and conventional machine learning methods. Have requisite theoretical strength, and expertise in problem solving whilst being hands on and be conversant with coding in Python along with relevant libraries. Qualifications/experience: PhD/Master’s/Graduate Degree in Computer Science, Machine ...

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 ...

positional encoding Experience working with temporal or sequential data, particularly from sensors or user interactions, wearables etc Comfortable managing experiments, model versions, and reproducible ML workflows Experience deploying machine learning models using cloud infrastructure (AWS preferred) Strong Python skills and a practical, delivery-focused mindset Desirable … device or in constrained environments Familiarity with representation learning or self-supervised approaches Research background or publications in relevant areas Tech stack • ML/AI: PyTorch, MLflow, SageMaker, ZenML • Infrastructure: AWS, Kubernetes, Docker • Edge deployment: CoreML, ONNX • Data: Python, S3, multimodal sensor data pipelines • Collaboration: JIRA, Git, structured ...

Lead Data Scientist | London | Retail or FinTech 📍 London (Hybrid) 💰 Up to £115,000 + Equity + Private Health Machine Learning | Data Science Libraries | Deep Learning Frameworks | AI Our client partners with some of the world’s most recognisable brands to deliver innovative, data-driven solutions that transform … Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) 💡 Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) 📈 Experienced project lead with strong technical decision-making and architecture ownership 🗣️ Excellent communicator — able to translate complex technical ...

LLMs) and machine learning security. Following a successful Series A funding round, they’re expanding their team and looking for a talented ML Scientist to help shape the future of intelligent, secure systems. You’ll be part of a strong research group located near King’s Cross, working … hybrid environment alongside accomplished ML scientists with publications at top-tier conferences. Experience Required MSc or PhD in Computer Science, Machine Learning, or a related discipline Strong hands-on experience with transformer-based models/LLMs Proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) Proven ...

Role - Machine Learning Engineer Location Hybrid, 1 day on site in London (with flex) Salary - £70,000 to £75,000 The Opportunity Were partnering with a client in the financial services sector who are looking to bring on a Machine Learning Engineer to their growing Intelligent ...

Urgent 12-month Hybrid AI/Machine Learning (ML) engineer role paying £400 a day inside IR35 in central London with 2-3 days in the office a week. Start before Christmas, I need to send candidates today for this to be possible. Interviews next week apply asap …/Today Key Responsibilities: Build and optimize AI/ML pipelines for predictive modelling, NLP, and generative AI applications. Perform Exploratory Data Analysis (EDA), data mining, and visualization to extract insights. Design and implement Big Data solutions using Hadoop, Spark, PySpark, and Data Lake architectures. Develop and deploy ML models ...

rolled out across a truly global legal organisation, shaping how advice is delivered to clients in 80+ countries worldwide. You’ll use data and machine learning to enhance legal processes, support strategic decision-making, and deliver forward-looking insights to an international client base. This includes designing innovative … data analysis, machine learning, and model development In-depth understanding of machine learning techniques, with experience delivering end-to-end ML solutions from initial build through to deployment Practical experience with data engineering, including designing and maintaining data pipelines, working with containerisation tools, and developing APIs ...

through to live deployment. What You’ll Be Doing: Designing, building and deploying production-ready AI and data science solutions Training and shipping advanced machine learning, deep learning and reinforcement learning models Developing AI systems using Large Language Models Building robust data pipelines for extraction, cleaning … data science solutions end to end Advanced Python skills with libraries such as Pandas, NumPy and scikit-learn Hands-on experience with machine learning techniques (e.g. tree-based models, regression) Practical exposure to deep learning and reinforcement learning approaches Experience working with SQL and structured data ...

high-profile consulting engagement with a major client in London. This is a fantastic opportunity to lead the design, implementation, and optimization of machine learning operations in a dynamic, multi-cloud environment. Key Responsibilities: Lead the end-to-end deployment … operationalization of machine learning models in production environments. Design and implement scalable MLOps pipelines, ensuring robust CI/CD practices for ML workflows. Collaborate closely with Data Scientists and Engineering teams to streamline model lifecycle management. Drive best practices for monitoring, versioning, and governance of ML models. Advise ...

reach of a global investment platform. Our team partners directly with internal investment desks as well as portfolio companies across industries to deliver machine learning solutions that unlock value and accelerate decision-making. Your work will range from developing and validating robust predictive models for pricing and valuation … forecasting, NLP, or optimization. Experience with uncertainty quantification, model evaluation, and statistical inference is highly valued. Python expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming ...

Type: Full-time | Permanent Salary: Up to £120k total compensation About Us We’re an ambitious technology company using advanced Machine Learning (ML) and Natural Language Processing (NLP) to power next-generation products. Until now, our AI projects have relied on third-party engines deployed via Docker … looking for an AI Infrastructure Lead — someone with the technical depth and vision to architect, implement, and scale an environment capable of supporting multiple ML and NLP initiatives across the business. The Role As our first senior AI hire, you’ll take ownership of designing and building the foundation ...

launch next year and are currently hiring in Miami, London and Milan. Role Contribution to production proprietary trading systems and create and deploy Machine Learning and Airtifical Intelligence models and experiment with trading ideas. Required Experience training Machine Learning models … from data processing to fine tuning), experience training across transformers/generative models/RL, with publications in either top tier ML conferences (e.g., NeurIPS, ICLR, ICML, JMLR, etc.) or top scientific journals, top tier institutions/industry experiences. Positives ...

value to their users. The team is building out scalable AI systems from the ground up, combining deep software engineering rigour with cutting-edge machine learning and retrieval techniques. You will work at the intersection of data engineering, AI product development, and platform reliability. This role suits someone … graph-based knowledge systems Track record of optimising and scaling AI systems to handle real-world loads with high reliability Knowledge of modern ML/LLM deployment workflows, including testing, infrastructure automation, and version control Exposure to frontend integration, particularly with frameworks like Angular, is a nice bonus Any experience ...

Fixed Income technology team, supporting electronic trading and market-making operations. This hybrid role combines software engineering with data science, building analytical tools, machine learning models, and data products that directly inform trading decisions and improve execution performance. You will work on the trading floor alongside traders, quants … historical data from electronic trading platforms including MarketAxess, Tradeweb, and Bloomberg, as well as internal order management and execution systems. The role involves developing machine learning models for applications such as trade flow prediction, execution quality analysis, client behaviour segmentation, and market pattern recognition. You will create interactive ...

Senior ML Engineer £50,000 to 60,000 GBP bonus Hybrid WORKING Location: Central London, Greater London - United Kingdom Type: Permanent Senior Machine Learning Engineer - London/Hybrid Up to £65,000 + DV Bonus | DV Eligible Required | No Sponsorship We are seeking a Senior ML Engineer … join a leading organisation delivering cutting-edge AI and machine learning solutions with real-world impact. You will design, develop, and deploy ML models, including traditional ML and GenAI/LLM applications, supporting national security and regulated sector objectives. This is a London-based role with hybrid working ...

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 ...

Intelligence, or a related field. Specialization in Natural Language Processing is preferred. Experience Requirements: 10 years+ of experience in developing Data Science, AI, and ML solutions, with a specific focus on generative AI and LLMs in the Finance/Telecomm/LSH/Manufacturing/Retail domain. Prior experience … identifying new opportunities to optimize the business through analytics, AI/ML and use case prioritization. The individual should be a thought leader having a well-balanced analytical business acumen, domain, and technical expertise. Large Language Model Expertise: Experience in working with and fine-tuning Large Language Models (LLMs), including ...

Agents) to Machine Learning problems (forecasting, classification, anomaly detection). The ideal candidate will have strong software engineering fundamentals alongside deep ML knowledge. Role: Architect & Build GenAI Systems: Design and deploy advanced RAG and GraphRAG applications ML Implementation: Develop and maintain traditional machine learning models (Regression … Python/TypeScript), manage CI/CD pipelines, and ensure scalable deployment via Docker and Kubernetes Infrastructure: Manage Vector Databases (Pinecone, Weaviate, Chroma) and ML model registries Experience: Experience: 3-5 years of professional engineering experience Core ML & Data Science: Proven experience applying traditional ML techniques (Random Forest, XGBoost, Linear ...

language understanding, reasoning, and workflow automation. Build agentic/LLM-driven workflows for multi-step decision making across diverse data sources. Architect and deliver ML features such as pattern recognition, entity extraction, and intelligent automation. Design scalable data and streaming pipelines capable of handling large, heterogeneous datasets. Build and optimize … systems to support high-quality retrieval. Deliver production-ready APIs, services, and model inference systems. Manage deployment, monitoring, observability, and continual improvement of ML models. Evaluate model performance using offline metrics, A/B tests, latency and cost optimisation. Work closely with product and domain experts to translate requirements into ...

Machine Learning Engineer Up to £75k Xcede have just started working with the UK’s leading financial advisor. Wanting to reinvent how the whole of the UK resolves financial disputes, you would be having a direct, visible impact allowing for people to receive money faster because of your … modern cloud platforms built and shipped serverless pipelines in a cloud environment (Azure preferred) experience building CI/CD pipelines Great understanding of various ML techniques and being able to explain them fully Prior experience in building production GenAI systems If you are interested in this or other Data Scientist ...

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 ...

organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps … Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability ...