1 to 25 of 474 Machine Learning Jobs in Central London

Machine Learning Engineer | Generative AI | AWS | End-to-End ML Solutions Location: London-based | Hybrid Please note: Sponsorship is not offered for this position We’re working with a leading organisation on a mission to become one of the most insight-driven businesses in its sector, placing machine learning and generative AI at the core of … customer experiences, operational optimisation, and strategic decision-making. This is a fantastic opportunity for a skilled Machine Learning Engineer to build and deploy scalable, production-level ML solutions, working closely with Data Scientists and cross-functional teams to drive measurable business impact. You’ll play a pivotal role in integrating machine learning models into end-to … ll also contribute to shaping the frameworks, infrastructure, and shared tooling that enable safe, responsible, and efficient AI experimentation and deployment. If you’re passionate about problem-solving, applying ML to real-world challenges, and bringing ideas to life in production environments, this role is a great fit. What You’ll Be Doing Machine Learning Engineering Build, deploy More ❯

Machine Learning Engineer | Generative AI | AWS | End-to-End ML Solutions Location: London-based | Hybrid Please note: Sponsorship is not offered for this position We’re working with a leading organisation on a mission to become one of the most insight-driven businesses in its sector, placing machine learning and generative AI at the core of … customer experiences, operational optimisation, and strategic decision-making. This is a fantastic opportunity for a skilled Machine Learning Engineer to build and deploy scalable, production-level ML solutions, working closely with Data Scientists and cross-functional teams to drive measurable business impact. You’ll play a pivotal role in integrating machine learning models into end-to … ll also contribute to shaping the frameworks, infrastructure, and shared tooling that enable safe, responsible, and efficient AI experimentation and deployment. If you’re passionate about problem-solving, applying ML to real-world challenges, and bringing ideas to life in production environments, this role is a great fit. What You’ll Be Doing Machine Learning Engineering Build, deploy More ❯

looking for Machine Learning Specialists, and we’re hoping it’s you! In this role, you’ll play a leading role in helping both customers with their ML validation challenges and in helping drive our product forward with insights on how to build the best validation solutions for high-stakes machine vision problems. The specific focus of … this position is on ML-based computer vision in high-stakes applications in Aviation, Mobility, Robotics and Edge Devices, with particular emphasis on object detection and tracking. The role has customer & user-facing elements working on real world problems to help ML teams (R&D and Product within other organizations) improve the quality of their models, but also requires deep … foundational knowledge on ML-based computer vision. In addition you will also work closely with the Safe Intelligence R&D team to help improve the company’s tools based on the challenges you see in your domains of expertise. This can range from inputs to product to working on the product itself. Previous contributions to state-of-the-art machine More ❯

looking for Machine Learning Specialists, and we’re hoping it’s you! In this role, you’ll play a leading role in helping both customers with their ML validation challenges and in helping drive our product forward with insights on how to build the best validation solutions for high-stakes machine vision problems. The specific focus of … this position is on ML-based computer vision in high-stakes applications in Aviation, Mobility, Robotics and Edge Devices, with particular emphasis on object detection and tracking. The role has customer & user-facing elements working on real world problems to help ML teams (R&D and Product within other organizations) improve the quality of their models, but also requires deep … foundational knowledge on ML-based computer vision. In addition you will also work closely with the Safe Intelligence R&D team to help improve the company’s tools based on the challenges you see in your domains of expertise. This can range from inputs to product to working on the product itself. Previous contributions to state-of-the-art machine More ❯

world challenges. In this role, you’ll: 🧠 Design, train, and evaluate machine learning and deep learning models for production environments 🛠 Develop and optimise end-to-end ML pipelines — from data preparation to model deployment 📊 Experiment with advanced generative and predictive models , including diffusion, autoregressive, and transformer-based architectures 🤝 Collaborate with data engineers and software developers to integrate … team that values experimentation and creative problem-solving 🏢 Hybrid Flexibility – Balance remote focus time with in-person collaboration at our London office 🌱 Learning Pathway – Gain exposure to advanced ML frameworks and progress toward senior engineering roles as you grow What We’re Looking For: 🎓 A degree in Artificial Intelligence, Computer Science, Mathematics, or a related field 🐍 Proficiency in Python … and innovation Nice to Have: 💾 Experience with JAX , Hydra , or Weights & Biases 📊 Exposure to GANs , diffusion models , or autoregressive architectures 📚 Knowledge of data privacy , machine unlearning , or secure ML methods 💻 Internship or academic project experience in AI research , data science , or software development If you’re ready to take your first step into applied machine learning and More ❯

world challenges. In this role, you’ll: 🧠 Design, train, and evaluate machine learning and deep learning models for production environments 🛠 Develop and optimise end-to-end ML pipelines — from data preparation to model deployment 📊 Experiment with advanced generative and predictive models , including diffusion, autoregressive, and transformer-based architectures 🤝 Collaborate with data engineers and software developers to integrate … team that values experimentation and creative problem-solving 🏢 Hybrid Flexibility – Balance remote focus time with in-person collaboration at our London office 🌱 Learning Pathway – Gain exposure to advanced ML frameworks and progress toward senior engineering roles as you grow What We’re Looking For: 🎓 A degree in Artificial Intelligence, Computer Science, Mathematics, or a related field 🐍 Proficiency in Python … and innovation Nice to Have: 💾 Experience with JAX , Hydra , or Weights & Biases 📊 Exposure to GANs , diffusion models , or autoregressive architectures 📚 Knowledge of data privacy , machine unlearning , or secure ML methods 💻 Internship or academic project experience in AI research , data science , or software development If you’re ready to take your first step into applied machine learning and More ❯

learning models and AI-driven solutions to address business challenges. Collaborate with data scientists to transition prototypes into production-ready systems . Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment. Optimise model performance, scalability, and reliability using MLOps best practices. Work with large-scale structured and unstructured datasets for model training and … validation. Implement model monitoring, versioning, and retraining processes to ensure continuous improvement. Collaborate cross-functionally with engineering, data, and product teams to integrate ML solutions into production environments. Stay current with emerging trends in AI/ML technologies and contribute to innovation within the organisation. Required Skills & Experience Proven experience (3–5+ years) as a Machine Learning Engineer … lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications Bachelor’s or Master’s degree in Computer Science , Data Science , Mathematics , or More ❯

learning models and AI-driven solutions to address business challenges. Collaborate with data scientists to transition prototypes into production-ready systems . Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment. Optimise model performance, scalability, and reliability using MLOps best practices. Work with large-scale structured and unstructured datasets for model training and … validation. Implement model monitoring, versioning, and retraining processes to ensure continuous improvement. Collaborate cross-functionally with engineering, data, and product teams to integrate ML solutions into production environments. Stay current with emerging trends in AI/ML technologies and contribute to innovation within the organisation. Required Skills & Experience Proven experience (3–5+ years) as a Machine Learning Engineer … lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications Bachelor’s or Master’s degree in Computer Science , Data Science , Mathematics , or More ❯

Machine learning Quantitative Engineer London - Hybrid working Rate - £1,200 Key Responsibilities Research, design, and implement machine learning and quantitative models for pricing, trading signals, and risk management across Fixed Income products (rates, credit, FX, mortgages). Apply advanced statistical learning methods (time-series, NLP, deep learning, reinforcement learning, graph-based models) to … to support production trading environments. Collaborate with traders, quants, and technologists to prototype and scale strategies from research to execution. Conduct rigorous backtesting, performance analysis, and explainability assessments of machine learning models. Contribute to the development of quantitative libraries and shared research infrastructure. Qualifications & Skills Essential: Strong expertise in machine learning, statistical modelling, and numerical methods …/TensorFlow) and experience with C++ or Java for high-performance model integration. Solid understanding of Fixed Income products, yield curve modelling, and financial mathematics. Experience building production-level ML systems in low-latency or large-scale environments. Strong communication skills with the ability to interact effectively with both technical and trading stakeholders. Desirable: Previous front-office or systematic trading More ❯

Machine learning Quantitative Engineer London - Hybrid working Rate - £1,200 Key Responsibilities Research, design, and implement machine learning and quantitative models for pricing, trading signals, and risk management across Fixed Income products (rates, credit, FX, mortgages). Apply advanced statistical learning methods (time-series, NLP, deep learning, reinforcement learning, graph-based models) to … to support production trading environments. Collaborate with traders, quants, and technologists to prototype and scale strategies from research to execution. Conduct rigorous backtesting, performance analysis, and explainability assessments of machine learning models. Contribute to the development of quantitative libraries and shared research infrastructure. Qualifications & Skills Essential: Strong expertise in machine learning, statistical modelling, and numerical methods …/TensorFlow) and experience with C++ or Java for high-performance model integration. Solid understanding of Fixed Income products, yield curve modelling, and financial mathematics. Experience building production-level ML systems in low-latency or large-scale environments. Strong communication skills with the ability to interact effectively with both technical and trading stakeholders. Desirable: Previous front-office or systematic trading More ❯

About Us We are a VC-backed startup focused on behavioural AI, currently in stealth. We are building for retail with a focus on Recommendation Systems, Reinforcement Learning and Generative AI. Our platform is designed from the ground up - no legacy, no patchwork systems - just a clean slate and a clear vision. Our mission is to build products that … customers love by harnessing cutting-edge AI to transform their shopping experience. About the Job We are looking for a Senior Data Scientist with experience in bringing advanced machine learning and data science systems to production to work with our team of industry leading domain experts and engineers. You'll be working across our entire data science stack … from advanced recommender systems to comprehensive performance analytics. Key Responsibilities: Design and implement scalable machine learning for complex data analysis, optimised recommendations, and predictive modelling. Translate the latest advances in machine learning into impactful solutions and products, from rapid MVPs to fully deployed, production-ready systems. Bring your models to production and optimise for inference in More ❯

About Us We are a VC-backed startup focused on behavioural AI, currently in stealth. We are building for retail with a focus on Recommendation Systems, Reinforcement Learning and Generative AI. Our platform is designed from the ground up - no legacy, no patchwork systems - just a clean slate and a clear vision. Our mission is to build products that … customers love by harnessing cutting-edge AI to transform their shopping experience. About the Job We are looking for a Senior Data Scientist with experience in bringing advanced machine learning and data science systems to production to work with our team of industry leading domain experts and engineers. You'll be working across our entire data science stack … from advanced recommender systems to comprehensive performance analytics. Key Responsibilities: Design and implement scalable machine learning for complex data analysis, optimised recommendations, and predictive modelling. Translate the latest advances in machine learning into impactful solutions and products, from rapid MVPs to fully deployed, production-ready systems. Bring your models to production and optimise for inference in More ❯

machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure seamless integration of ML models into products. … Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration … with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience More ❯

machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure seamless integration of ML models into products. … Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration … with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience More ❯

customers get maximum value out of our solutions. The ideal candidate for this role will get stuck in across the organisation, moving naturally from intricate data analysis, through detailed ML considerations and onto the broader business context. You will have the freedom to propose, research and implement innovative new ideas to improve our system. If you want to apply cutting … have immediate business impact, we’d love to hear from you. Your responsibilities Innovate on Solvo’s modelling and decision making solution. Create value for customers through application of ML principles and best practice. Strive for high quality and robust outcomes. Continuously ensure we are using the most appropriate ML modelling techniques for customer projects and our product offerings. Design … scalability and performance. Collaborate closely with scientists and engineers in an agile team environment. Facilitate understanding of our AI solutions internally and externally. Continuously develop your own AI/ML and engineering skills. Essential skills and experience Academic or industrial research experience in machine learning, especially probabilistic models and Bayesian statistics. Proficiency in designing and programming advanced ML More ❯

customers get maximum value out of our solutions. The ideal candidate for this role will get stuck in across the organisation, moving naturally from intricate data analysis, through detailed ML considerations and onto the broader business context. You will have the freedom to propose, research and implement innovative new ideas to improve our system. If you want to apply cutting … have immediate business impact, we’d love to hear from you. Your responsibilities Innovate on Solvo’s modelling and decision making solution. Create value for customers through application of ML principles and best practice. Strive for high quality and robust outcomes. Continuously ensure we are using the most appropriate ML modelling techniques for customer projects and our product offerings. Design … scalability and performance. Collaborate closely with scientists and engineers in an agile team environment. Facilitate understanding of our AI solutions internally and externally. Continuously develop your own AI/ML and engineering skills. Essential skills and experience Academic or industrial research experience in machine learning, especially probabilistic models and Bayesian statistics. Proficiency in designing and programming advanced ML More ❯

years’ experience in machine learning engineering, with demonstrable expertise in: Natural Language Processing (NLP), information extraction, and working with large language models (LLMs) Python programming and major ML frameworks such as PyTorch or TensorFlow MLOps practices including containerisation (Docker), orchestration (Kubernetes), and CI/CD pipelines tailored for ML workflows Utilising AI-enhanced development environments and tools to … s or PhD) in computer science or a related field Experience in training and deploying LLMs at scale Familiarity with cloud infrastructure and distributed computing environments Exposure to modern ML tooling such as Modal, Weights & Biases, or Amazon SageMaker Knowledge of fine-tuning techniques including LoRA, QLoRA, or other parameter-efficient frameworks Role Overview The successful candidate will be responsible … Customising and refining LLMs for specific business applications, ensuring optimal performance and scalability Collaborating with data engineering teams to prepare and transform large datasets for model training Building robust ML services with monitoring, retraining, and performance tracking capabilities Enhancing the organisation’s MLOps infrastructure, including model lifecycle management and evaluation systems Partnering with product and engineering teams to embed ML More ❯

About the Opportunity: We are seeking an ambitious and intellectually curious Junior Data Scientist to join a fast-growing, forward-thinking team working at the forefront of data science, machine learning, and applied AI. This is an excellent opportunity for a recent Master’s graduate eager to apply their academic expertise to solving real-world challenges—whether it … s predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What You’ll Be Doing: Designing and building machine learning models to solve real-world … B testing Presenting findings clearly to both technical and non-technical stakeholders Collaborating across data science, engineering, and product teams to build scalable solutions Staying current with advancements in machine learning and AI, and contributing new ideas to internal R&D discussions What We’re Looking For: A recently completed Master’s degree from a Russell Group university More ❯

About the Opportunity: We are seeking an ambitious and intellectually curious Junior Data Scientist to join a fast-growing, forward-thinking team working at the forefront of data science, machine learning, and applied AI. This is an excellent opportunity for a recent Master’s graduate eager to apply their academic expertise to solving real-world challenges—whether it … s predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What You’ll Be Doing: Designing and building machine learning models to solve real-world … B testing Presenting findings clearly to both technical and non-technical stakeholders Collaborating across data science, engineering, and product teams to build scalable solutions Staying current with advancements in machine learning and AI, and contributing new ideas to internal R&D discussions What We’re Looking For: A recently completed Master’s degree from a Russell Group university More ❯

AI Engineer at Principal/Staff level to build and to deliver an AI capability. Responsibilities Reporting to VP Engineering Lead design, architecture, and delivery of advanced AI/ML and generative AI solutions, ensuring scalable, secure, and production-ready system. Expert in MCP and RAG patterns Design and build robust data and ingestion pipelines, integrate vector databases, and RSG. … Expert-level proficiency in Python and key ML libraries (Langchain, Semantic Kernel, PyTorch, TensorFlow) Hands-on experience with cloud platforms (Azure, AWS) and infrastructure-as-code (Terraform, ECS) Strong background in deploying models via APIs, containers, or cloud-native services Proven track record delivering production-grade AI solutions in complex, data-rich environments Skilled in setting team engineering practices: Git … CI/CD, automated testing for ML code, code reviews, and documentation. Lead tech enablement and mentor engineers, fostering culture of reliability, continuous improvement, and collaboration. Excellent communication skills, able to translate technical strategy into business outcomes and work across team. Minimum 5 years’ professional experience in AI, ML, or applied machine learning engineering roles. Required Skills Expert More ❯

AI Engineer at Principal/Staff level to build and to deliver an AI capability. Responsibilities Reporting to VP Engineering Lead design, architecture, and delivery of advanced AI/ML and generative AI solutions, ensuring scalable, secure, and production-ready system. Expert in MCP and RAG patterns Design and build robust data and ingestion pipelines, integrate vector databases, and RSG. … Expert-level proficiency in Python and key ML libraries (Langchain, Semantic Kernel, PyTorch, TensorFlow) Hands-on experience with cloud platforms (Azure, AWS) and infrastructure-as-code (Terraform, ECS) Strong background in deploying models via APIs, containers, or cloud-native services Proven track record delivering production-grade AI solutions in complex, data-rich environments Skilled in setting team engineering practices: Git … CI/CD, automated testing for ML code, code reviews, and documentation. Lead tech enablement and mentor engineers, fostering culture of reliability, continuous improvement, and collaboration. Excellent communication skills, able to translate technical strategy into business outcomes and work across team. Minimum 5 years’ professional experience in AI, ML, or applied machine learning engineering roles. Required Skills Expert More ❯

processing, and post processing. Mentor and work with junior scientists to research and deliver innovative technologies that utilize every bit of signal in the data. Participate in hands-on machine learning research and deliver the results of the research in the form of new products. Communicate technical vision and roadmap at multiple levels within the organisation and externally. … journals. Represent Entrust at national and international scientific conferences. Contribute to filing patents. Essential Skills: Strong experience in machine learning and computer vision, including industry experience deploying ML models to production. Track record of successfully delivering high performance ML-driven products. Worked with customers to impactfully solve their problems. Deep understanding of machine learning theory. Strong … coding skills in Python and hands on experience using at least one of the deep learning frameworks Tensorflow or PyTorch. Desirable Skills: Technical experience in uncertainty modelling, explainable machine learning techniques, out-of-distribution detection, life-long learning, and related fields. Technical experience with signal processing and image processing techniques. Working knowledge of cloud computing (preferably 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 ❯

Team: Machine Learning Location: London (On-site; Liverpool Street) Employment Type: Full-time and Permanent Remuneration: £120 - 160k Base Salary + Discretionary Bonus + Equity We are a stealth-mode AI laboratory researching and developing Machine Learning models. The founding team consists of Cambridge graduates and former engineers at Google, Meta, Bloomberg, Microsoft and Amazon. We … from the US and the UK, including institutional VC funds and C-level executives of global technology companies. In this role, you will: Design, develop and train large multimodal machine learning models across all stages: pre-training, post-training, evaluations and inference. Work closely with clients to understand data and model architecture requirements for their business needs. Be … that is perfectly fine. If you are passionate about data and enjoy solving complex challenges, we would love to hear from you. Nice to have: Publications: At top-tier ML/CV/NLP conferences (NeurIPS, ICML, ICLR, CVPR, ICCV) Open-source: Contributions to and experience in open-source projects. Startup experience: Experience with a startup work environment and wider More ❯