1 to 25 of 310 Machine Learning Jobs in Central London

and maintaining machine learning systems that drive data-driven decision-making in the pensions and financial services sector. Using Azure's cloud ecosystem, you will build scalable ML workflows that support actuarial modelling, risk prediction, and client insight generation. Key Responsibilities 1. Azure-Based Machine Learning Development * Collaborate with domain experts and analysts to design and … implement machine learning models that predict key outcomes such as life expectancy, investment return scenarios, and financial risks. * Deploy and manage ML solutions using Azure Machine Learning (Azure ML), covering training, testing, and deployment to production. * Select appropriate ML techniques (e.g., classification, regression, ensemble methods, survival models) to improve predictions and automate core processes. 2. MLOps … Model Lifecycle Management * Own the end-to-end ML lifecycle using Azure ML pipelines, Data Factory (ADF), and ML tracking tools. * Implement CI/CD pipelines with Azure DevOps, ensuring robust version control, testing, and seamless deployment. * Monitor production ML systems for performance, data drift, and anomalies using Azure Monitor or other observability tools. * Schedule and automate model retraining pipelines More ❯

Positions: Machine Learning Engineer & Machine Learning Researcher My client is a scaling robotics start-up that is creating autonomous industrial robots capable of handling intricate, dexterous tasks. They're looking for Senior ML Engineers who want the freedom to bridge the gap between state-of-the-art research in embodied AI and real-world systems. You'll be joining a team of accomplished … and industrial know-how, who will help nurture and develop you to the next level! Salary: Up to £150k Location: London Onsite: Most days What You’ll Be Doing (Machine Learning Engineer): Implement and scale state-of-the-art AI algorithms to be deployed on real-world robotic systems Build robust data pipelines and work with multi-modal More ❯

Positions: Machine Learning Engineer & Machine Learning Researcher My client is a scaling robotics start-up that is creating autonomous industrial robots capable of handling intricate, dexterous tasks. They're looking for Senior ML Engineers who want the freedom to bridge the gap between state-of-the-art research in embodied AI and real-world systems. You'll be joining a team of accomplished … and industrial know-how, who will help nurture and develop you to the next level! Salary: Up to £150k Location: London Onsite: Most days What You’ll Be Doing (Machine Learning Engineer): Implement and scale state-of-the-art AI algorithms to be deployed on real-world robotic systems Build robust data pipelines and work with multi-modal More ❯

in developing new index methodologies. 🧠 About the Role Scientific Beta is seeking a highly experienced and innovative Lead Expert in Natural Language Processing (NLP) and Machine Learning (ML) to spearhead the development of next-generation sustainability and financial metrics. This is a unique opportunity to leverage cutting-edge language models and insights at the intersection of empirical finance … driving the research, development, validation and product implementation of novel metrics by extracting valuable information from textual data. 📌 Key Responsibilities Lead the conceptualization, design, and implementation of NLP and ML models for extracting insights related to sustainability and financial performance from diverse textual sources. Develop and apply state-of-the-art language models to extract relevant information and integrate academic … financial applications would be an advantage. • Advanced degree (MSc. or Ph.D.) in Data Science, Computer Science, Computational Linguistics or a related quantitative field with a focus on NLP/ML techniques. More ❯

in developing new index methodologies. 🧠 About the Role Scientific Beta is seeking a highly experienced and innovative Lead Expert in Natural Language Processing (NLP) and Machine Learning (ML) to spearhead the development of next-generation sustainability and financial metrics. This is a unique opportunity to leverage cutting-edge language models and insights at the intersection of empirical finance … driving the research, development, validation and product implementation of novel metrics by extracting valuable information from textual data. 📌 Key Responsibilities Lead the conceptualization, design, and implementation of NLP and ML models for extracting insights related to sustainability and financial performance from diverse textual sources. Develop and apply state-of-the-art language models to extract relevant information and integrate academic … financial applications would be an advantage. • Advanced degree (MSc. or Ph.D.) in Data Science, Computer Science, Computational Linguistics or a related quantitative field with a focus on NLP/ML techniques. More ❯

Are you a Junior Machine Learning Engineer eager to turn messy, complex data into real-world intelligence? We’re looking for a curious and motivated Junior ML Engineer to join a hybrid-working team building cutting-edge data intelligence tools for the financial sector. You’ll spend part of your time collaborating in person with engineers and data … remotely — giving you the best of both worlds. You’ll be working on a platform that transforms unstructured private market data into actionable insights — learning how to design ML pipelines, fine-tune NLP models, and deploy solutions that really work in production. In this role, you’ll help train, test, and optimise models that can read, understand, and structure … world clients. What’s in it for you? 📄 AI That Matters – Work on models that make sense of unstructured financial documents and turn them into structured insights. ⚙ Hands-On ML Experience – Learn the full ML workflow — from cleaning data to deploying models and monitoring them in production. 📈 Mentorship & Growth – Work closely with experienced ML engineers who will guide your technical More ❯

Are you a Junior Machine Learning Engineer eager to turn messy, complex data into real-world intelligence? We’re looking for a curious and motivated Junior ML Engineer to join a hybrid-working team building cutting-edge data intelligence tools for the financial sector. You’ll spend part of your time collaborating in person with engineers and data … remotely — giving you the best of both worlds. You’ll be working on a platform that transforms unstructured private market data into actionable insights — learning how to design ML pipelines, fine-tune NLP models, and deploy solutions that really work in production. In this role, you’ll help train, test, and optimise models that can read, understand, and structure … world clients. What’s in it for you? 📄 AI That Matters – Work on models that make sense of unstructured financial documents and turn them into structured insights. ⚙ Hands-On ML Experience – Learn the full ML workflow — from cleaning data to deploying models and monitoring them in production. 📈 Mentorship & Growth – Work closely with experienced ML engineers who will guide your technical More ❯

We’re Hiring: Data Scientist/Machine Learning Engineer Location: Sheffield/London (hybrid) Employment Type: Contract We are seeking a highly skilled Data Scientist/Machine Learning Engineer to join our team. This role involves working with large datasets, applying advanced analytics, and building predictive models to drive actionable business insights. Responsibilities: Preprocess structured and … include all relevant information for analytic systems Process, cleanse, and validate the integrity of data Analyze large volumes of data to identify patterns and solutions Develop predictive systems and machine learning algorithms Present analytical results clearly to stakeholders Propose solutions and strategies for business challenges Perform data mining and extract usable insights from multiple data sources Use machine … stack (VMs, middleware like IIS/Apache, hypervisors, databases, etc.) and OTLP formatting/structuring Ability to correlate streaming OLTP data from multiple components and generate actionable insights using ML models Strong analytical and problem-solving skills Experience with feature selection, classifier creation, and optimization More ❯

We’re Hiring: Data Scientist/Machine Learning Engineer Location: Sheffield/London (hybrid) Employment Type: Contract We are seeking a highly skilled Data Scientist/Machine Learning Engineer to join our team. This role involves working with large datasets, applying advanced analytics, and building predictive models to drive actionable business insights. Responsibilities: Preprocess structured and … include all relevant information for analytic systems Process, cleanse, and validate the integrity of data Analyze large volumes of data to identify patterns and solutions Develop predictive systems and machine learning algorithms Present analytical results clearly to stakeholders Propose solutions and strategies for business challenges Perform data mining and extract usable insights from multiple data sources Use machine … stack (VMs, middleware like IIS/Apache, hypervisors, databases, etc.) and OTLP formatting/structuring Ability to correlate streaming OLTP data from multiple components and generate actionable insights using ML models Strong analytical and problem-solving skills Experience with feature selection, classifier creation, and optimization More ❯

global impact, and ready to excel in a dynamic, high-energy environment. Join our team and help shape the future of Vision AI. 🌎 Location and Legalities This full-time Machine Learning Engineer position is based onsite in our brand-new Ultralytics office in London, UK. Applicants must have legal authorization to work in the UK, as Ultralytics does … not provide visa sponsorship. 🚀 What You'll Do As a Machine Learning Engineer at Ultralytics, you will be at the forefront of developing and refining our world-class Ultralytics YOLO models. You will work on the entire lifecycle of our models, from research and development to high-performance deployment. Key responsibilities include: Developing, training, and validating state-of … critical in advancing the capabilities of our models and supporting Ultralytics' mission to make AI easy and accessible for everyone. 🛠️ Skills and Experience 5+ years of professional experience in Machine Learning Engineering or a similar role. Deep expertise in Python and deep learning frameworks, with a strong preference for PyTorch. Proven experience with computer vision and a More ❯

global impact, and ready to excel in a dynamic, high-energy environment. Join our team and help shape the future of Vision AI. 🌎 Location and Legalities This full-time Machine Learning Engineer position is based onsite in our brand-new Ultralytics office in London, UK. Applicants must have legal authorization to work in the UK, as Ultralytics does … not provide visa sponsorship. 🚀 What You'll Do As a Machine Learning Engineer at Ultralytics, you will be at the forefront of developing and refining our world-class Ultralytics YOLO models. You will work on the entire lifecycle of our models, from research and development to high-performance deployment. Key responsibilities include: Developing, training, and validating state-of … critical in advancing the capabilities of our models and supporting Ultralytics' mission to make AI easy and accessible for everyone. 🛠️ Skills and Experience 5+ years of professional experience in Machine Learning Engineering or a similar role. Deep expertise in Python and deep learning frameworks, with a strong preference for PyTorch. Proven experience with computer vision and a More ❯

and computer vision models for medical use. Design, implement, and optimize data processing pipelines across structured and unstructured healthcare datasets, including real-time imaging. Translate clinical needs into ML/AI solutions, working closely with cross-disciplinary teams including clinicians, mechanical engineers, software engineers, and regulatory experts. Architect and deliver AI systems that meet performance, safety, and regulatory standards … for real-world use. Mentor junior engineers and scientists, promoting best practices in software architecture, model reproducibility, and data pipeline automation. Define and execute the AI/ML/data roadmap: data governance, cloud-based MLOps, model validation, scalability, and deployment strategy. Ensure data security, privacy, and compliance in all aspects of model development and deployment. Integrate with data scientists … computer vision, especially for real-time applications Proficiency in Python and C++ Proven experience with large-scale datasets, particularly healthcare and clinical imaging data. Strong understanding of AI/ML platforms, libraries, and best practices (e.g., PyTorch, TensorFlow, OpenCV). Proficiency with databases (SQL/NoSQL), data versioning, and source control (Git/GitHub). Demonstrated ability to build, deploy More ❯

and computer vision models for medical use. Design, implement, and optimize data processing pipelines across structured and unstructured healthcare datasets, including real-time imaging. Translate clinical needs into ML/AI solutions, working closely with cross-disciplinary teams including clinicians, mechanical engineers, software engineers, and regulatory experts. Architect and deliver AI systems that meet performance, safety, and regulatory standards … for real-world use. Mentor junior engineers and scientists, promoting best practices in software architecture, model reproducibility, and data pipeline automation. Define and execute the AI/ML/data roadmap: data governance, cloud-based MLOps, model validation, scalability, and deployment strategy. Ensure data security, privacy, and compliance in all aspects of model development and deployment. Integrate with data scientists … computer vision, especially for real-time applications Proficiency in Python and C++ Proven experience with large-scale datasets, particularly healthcare and clinical imaging data. Strong understanding of AI/ML platforms, libraries, and best practices (e.g., PyTorch, TensorFlow, OpenCV). Proficiency with databases (SQL/NoSQL), data versioning, and source control (Git/GitHub). Demonstrated ability to build, deploy More ❯

the entire delivery lifecycle—from design and development to testing, deployment, and ongoing support. You will work across the full machine learning workflow, applying advanced analytics and ML techniques to extract structured insights from complex insurance submission documents, conduct exposure analytics, and model asset behaviour for the commercial insurance market. Responsibilities Design, build, and deploy machine learning … in version control, testing, CI/CD, and MLOps Share expertise through peer code reviews, documentation, and collaborative learning initiatives Stay current with emerging trends in AI/ML, particularly in areas such as LLMs, NLP, and intelligent document automation What skills and experience will I need to bring with me? You’ll need to be able to demonstrate … all the skills, you have a passion and willingness for learning. Here’s what the teams will be looking for: 3–5 years of professional experience in data science ML, or applied AI role Strong problem-solving and analytical skills with the ability to approach complex technical challenges independently Proven experience in building, deploying, and maintaining ML models in production More ❯

Manage multiple projects from inception to deployment within cloud-based environments. Maintain high standards in code review, documentation, and delivery in a DevOps context. Apply a deep understanding of ML techniques, from supervised/unsupervised learning to generative AI and large language models. What We’re Looking For Essential Skills and Experience: Proven ability to solve complex, real-world … Experience managing multiple end-to-end data science projects across varied data types. Familiarity with DevOps practices and tools like Git. Cloud experience (e.g. Azure, AWS) and working with ML platforms and services. Strong communication skills, capable of explaining complex topics to non-technical stakeholders. Ability to align data science efforts with broader business objectives. Desirable Skills: Experience using R … and NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations or regulated industries. Strong working knowledge of Excel, SQL, Power BI More ❯

Manage multiple projects from inception to deployment within cloud-based environments. Maintain high standards in code review, documentation, and delivery in a DevOps context. Apply a deep understanding of ML techniques, from supervised/unsupervised learning to generative AI and large language models. What We’re Looking For Essential Skills and Experience: Proven ability to solve complex, real-world … Experience managing multiple end-to-end data science projects across varied data types. Familiarity with DevOps practices and tools like Git. Cloud experience (e.g. Azure, AWS) and working with ML platforms and services. Strong communication skills, capable of explaining complex topics to non-technical stakeholders. Ability to align data science efforts with broader business objectives. Desirable Skills: Experience using R … and NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations or regulated industries. Strong working knowledge of Excel, SQL, Power BI More ❯

challenges, whether it’s extracting structured data from contracts, building predictive models for compliance risk, or uncovering patterns in complex legal datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and legal subject-matter experts to design, develop, and deploy models that transform how organisations interact with legal information. What You’ll Be Doing: Designing and … building machine learning and NLP models to process and analyse large volumes of legal and business text. Carrying out full data science workflows: from data acquisition and cleaning to modelling, validation, and deployment. Applying statistical, deep learning, and neuro-symbolic AI techniques to generate actionable insights. Contributing to experimental research, model prototyping, and performance benchmarking. Presenting findings … building a compliance risk prediction tool using large language models. Strong programming skills in Python (NumPy, pandas, scikit-learn, matplotlib); R is also welcome. A solid understanding of core ML concepts, NLP techniques, data wrangling, and model evaluation. Proficiency with SQL and experience handling large, unstructured datasets. A passion for solving complex problems using data and a continuous learning More ❯

challenges, whether it’s extracting structured data from contracts, building predictive models for compliance risk, or uncovering patterns in complex legal datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and legal subject-matter experts to design, develop, and deploy models that transform how organisations interact with legal information. What You’ll Be Doing: Designing and … building machine learning and NLP models to process and analyse large volumes of legal and business text. Carrying out full data science workflows: from data acquisition and cleaning to modelling, validation, and deployment. Applying statistical, deep learning, and neuro-symbolic AI techniques to generate actionable insights. Contributing to experimental research, model prototyping, and performance benchmarking. Presenting findings … building a compliance risk prediction tool using large language models. Strong programming skills in Python (NumPy, pandas, scikit-learn, matplotlib); R is also welcome. A solid understanding of core ML concepts, NLP techniques, data wrangling, and model evaluation. Proficiency with SQL and experience handling large, unstructured datasets. A passion for solving complex problems using data and a continuous learning More ❯

Graduate Technical Recruiter - Trading Technology & Machine Learning About Algo Capital: Algo Capital is a leading global algorithmic talent firm specializing in Quantitative Trading and Trading Technology recruitment across the US, EMEA, and APAC. We partner with the most exclusive clients in the trading industry, who are pushing the boundaries of AI, machine learning, and low-latency … of the art solutions and platforms. We're seeking a driven Graduate Technical Recruiter to join our team, focusing on C++, Python, Low Latency systems, and advanced AI/ML roles. Who You Are: Recent STEM or related field graduate with a strong interest in technical recruitment for Finance, Trading Technology, or FinTech Entrepreneurial mindset Eager to learn about recruiting … Comprehensive training (1:1 mentorship) in Trading Technology and AI recruitment Collaborative, high performing team culture Networking with top-tier professionals and technologists in Trading Technology and AI/ML Clear structured career progression path in Quantitative technical recruitment This is an excellent opportunity to build a lasting career in quantitative technology, if you would like further information please apply More ❯

a top-tier quantitative firm. International Talent: Yes, international applicants are encouraged. These roles are for a professional with a global perspective, ready to apply their sophisticated expertise in machine learning to London’s prestigious financial markets. Are you interested in joining environments where your research will directly influence strategies with a substantial AUM? Individuals who are seeking … the future of quantitative and discretionary trading should take this opportunity seriously. 🔷 The Profile – Your Expertise We’re looking for professionals with a global perspective, skilled in applying advanced machine learning techniques to financial data. They have a demonstrable history of developing and deploying sophisticated models in institutional settings, with deep expertise in risk … management and the ability to integrate cutting-edge research into scalable, robust trading platforms that meet the highest standards of institutional finance. Career Path: Career trajectories focused on applying ML to solve complex problems in global, institutional trading environments. Histories of delivering high-impact projects that directly influence multi-million-dollar portfolios. Projects And Performance: Experience developing models for global More ❯

a top-tier quantitative firm. International Talent: Yes, international applicants are encouraged. These roles are for a professional with a global perspective, ready to apply their sophisticated expertise in machine learning to London’s prestigious financial markets. Are you interested in joining environments where your research will directly influence strategies with a substantial AUM? Individuals who are seeking … the future of quantitative and discretionary trading should take this opportunity seriously. 🔷 The Profile – Your Expertise We’re looking for professionals with a global perspective, skilled in applying advanced machine learning techniques to financial data. They have a demonstrable history of developing and deploying sophisticated models in institutional settings, with deep expertise in risk … management and the ability to integrate cutting-edge research into scalable, robust trading platforms that meet the highest standards of institutional finance. Career Path: Career trajectories focused on applying ML to solve complex problems in global, institutional trading environments. Histories of delivering high-impact projects that directly influence multi-million-dollar portfolios. Projects And Performance: Experience developing models for global More ❯

possesses practical expertise in machine learning, with experience across the full lifecyclefrom business scoping and data engineering through to deployment, monitoring, and ethical considerations. Familiar with classical ML techniques (e.g., regression, classification, clustering), as well as deep learning, NLP, transfer learning, and recent advancements in LLMs and generative AI. Able to contextualise these techniques in industry … settings, such as financial forecasting, operations optimisation, or customer segmentation. Comfortable with key ML frameworks (such as Scikit-learn, TensorFlow, PyTorch, Hugging Face) and data manipulation tools (Pandas, NumPy), as well as version control, containerisation, and ML deployment pipelines. Understands how to apply MLOps principles in production environments To be successful in this role you must have hands-on experience … designing and deploying ML models in industryideally within agile or cross-functional teams. Understands what it takes to build and maintain scalable, ethical, and production-ready AI systems. Can share personal stories of both success and failure in deploying ML, helping learners understand real-world challenges like stakeholder alignment, data quality, model drift, or technical debt in pipelines. Ideally, has More ❯

days in office) Up to £125,000 + Equity About the Role A fast-scaling climate tech company backed by investors is looking for a Director of AI & ML to lead the development of advanced machine learning solutions that help global banks, insurers, and real estate firms understand and act on physical climate risk. You’ll define the … ML strategy, shape a high-impact team, and deliver real-world innovation across generative AI, geospatial modelling, and time-series forecasting. Key Responsibilities Own and evolve the company’s AI & ML strategy in line with product and customer priorities Lead, mentor, and grow a high-performing team of ML Engineers Take prototypes through to production, delivering meaningful product features powered … by GenAI and predictive modelling Collaborate with Science and Engineering to integrate ML with physics-based climate models Communicate complex technical concepts in simple, outcome-oriented terms for customers and cross-functional teams Your work will focus on delivering high-value insights and solutions, including: Developing generative AI tools for geospatial risk assessment Building models to project the impact of More ❯

research and high-performance trading. You’ll join a highly skilled Research Engineering team, in a fast-moving, high-volume environment. This role is all about taking cutting-edge ML research projects and moving them into production — building robust pipelines that allow models to trade with reliability and speed. You’ll be hands-on with code (around 80% of your … time), collaborating closely with ML scientists, and owning solutions from ingestion to deployment. Key Responsibilities Collaborate with ML scientists to ingest and process large-scale, high-frequency market data. Build and maintain pipelines for training, backtesting, and deploying ML models into a live trading environment. Ensure production systems are reliable, scalable, and optimised for ultra-low latency trading. Take ownership … of end-to-end solutions, from research to execution. What We’re Looking For 5+ years’ experience in high-level engineering roles. Proven track record building ML research pipelines in complex technical environments. Experience in Python (and ideally C++) plus Kubernetes, Ray, PyTorch, Terraform, and cloud platforms (AWS, GCP, or Azure). Strong mathematical or statistical background. Background in AI More ❯

research and high-performance trading. You’ll join a highly skilled Research Engineering team, in a fast-moving, high-volume environment. This role is all about taking cutting-edge ML research projects and moving them into production — building robust pipelines that allow models to trade with reliability and speed. You’ll be hands-on with code (around 80% of your … time), collaborating closely with ML scientists, and owning solutions from ingestion to deployment. Key Responsibilities Collaborate with ML scientists to ingest and process large-scale, high-frequency market data. Build and maintain pipelines for training, backtesting, and deploying ML models into a live trading environment. Ensure production systems are reliable, scalable, and optimised for ultra-low latency trading. Take ownership … of end-to-end solutions, from research to execution. What We’re Looking For 5+ years’ experience in high-level engineering roles. Proven track record building ML research pipelines in complex technical environments. Experience in Python (and ideally C++) plus Kubernetes, Ray, PyTorch, Terraform, and cloud platforms (AWS, GCP, or Azure). Strong mathematical or statistical background. Background in AI More ❯