1 to 25 of 223 Permanent Machine Learning Jobs in Central London

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 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 ❯

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 ❯

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 ❯

Back End Engineer - Java, Python, AWS, MySQL, NoSql, REST APIs, Microservices, Machine Learning, Artificial intelligence (Remote or Hybrid - You choose!) Back End Engineer:- You will be joining a fast-growing, research-driven company building an artificial intelligence using novel machine learning techniques. My client is revolutionising their industry with a track record of building things that … knowledge of Cloud Technologies (AWS) and Microservices Degree in Computer Science, Engineering, or a related field, or equivalent hands-on experience in engineering. Experience or interest in AI or Machine Learning Salary for the Back End Engineer (Java) will depend on experience, but expect between £50,000 and £70,000 + Pension + benefits Other benefits include:- Free … games etc.) The latest tech, generous annual leave and an amazing office with a balcony overlooking Notting Hill. Back End Engineer - Java, Python, AWS, MySQL, NoSql, REST APIs, Microservices, Machine Learning, Artificial intelligence (Remote or Hybrid - You choose!) Applicants must have the right to work in the UK, no sponsorship is offered for this role 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 ❯

help us make this vision a reality. Competitive candidates will have a track record of writing and shipping quality, well-documented and well-tested software in the AI/ML industry. We are looking for candidates with experience in the field of Responsible AI, preferably for generative AI or language applications. In addition to ML engineering and data science skills … large team. Our leaders will be committed to your career and development from day one. Key responsibilities Back end development for a Python web application Integration of AI/ML components with frontend, backend, data and compute infrastructure Responsible for high quality software implementations according to best practices, including automated test suites and documentation Develop, measure, and monitor key metrics … Docker or containerized applications, especially architecture of multi-container applications Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience Knowledge of AI/ML approaches and deployment of AI/ML powered applications – especially using language models or NLP and agent-based approaches (e.g. LangGraph, PydanticAI, AutoGen) Knowledge of AI/ML evaluation and More ❯

help us make this vision a reality. Competitive candidates will have a track record of writing and shipping quality, well-documented and well-tested software in the AI/ML industry. We are looking for candidates with experience in the field of Responsible AI, preferably for generative AI or language applications. In addition to ML engineering and data science skills … large team. Our leaders will be committed to your career and development from day one. Key responsibilities Back end development for a Python web application Integration of AI/ML components with frontend, backend, data and compute infrastructure Responsible for high quality software implementations according to best practices, including automated test suites and documentation Develop, measure, and monitor key metrics … Docker or containerized applications, especially architecture of multi-container applications Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience Knowledge of AI/ML approaches and deployment of AI/ML powered applications – especially using language models or NLP and agent-based approaches (e.g. LangGraph, PydanticAI, AutoGen) Knowledge of AI/ML evaluation and More ❯

Senior Data Scientist Ai ML Python MML Japanese & English Speaking Working Pattern: Hybrid (12 days per week in office) Location: London The Data Science function plays a pivotal role in delivering advanced Artificial Intelligence capabilities across the organisation. This position focuses on designing, developing, and deploying production-grade machine learning solutions while contributing to the strategic growth of … team and collaborate closely with Software Engineers, Product Managers, and other stakeholders. The role requires strong mathematical and statistical foundations, excellent software engineering skills, and proven expertise in modern machine learning techniques, including Computer Vision, Natural Language Processing … and Deep Learning. ---------------------------------------- Key Responsibilities Design, build, and deploy advanced machine learning models and algorithms into production. Lead technical development within cross-functional teams, providing guidance on ML solution design and implementation. Translate business problems into clearly defined data science solutions and deliver end-to-end ML pipelines. Support proof-of-value initiatives and contribute to product roadmap More ❯

be themselves. Position Overview: You will join the Entrust Applied Science team as a research intern. The team consists of 20+ Applied Scientists located in London, UK. We develop machine learning and computer vision models for the Onfido product lines, in particular fraud detection and data extraction on government IDs and biometrics data. You will work together with … a team of scientist who will coach and train you during your internship. We use state-of-the-art technology (deep learning, VLMs), own a large proprietary dataset of images and videos and use a multi-GPU cluster. We use standard frameworks (python, pytorch, tensorflow, dask, AWS). We impact production directly but also the machine learning … and train models on state-of-the-art GPUs Your work will impact products used by dozens of millions of users worldwide You will be mentored by a senior machine learning scientist to make sure you are successful in your mission You will have the opportunity to publish and open-source your work You will be part of More ❯

be themselves. Position Overview: You will join the Entrust Applied Science team as a research intern. The team consists of 20+ Applied Scientists located in London, UK. We develop machine learning and computer vision models for the Onfido product lines, in particular fraud detection and data extraction on government IDs and biometrics data. You will work together with … a team of scientist who will coach and train you during your internship. We use state-of-the-art technology (deep learning, VLMs), own a large proprietary dataset of images and videos and use a multi-GPU cluster. We use standard frameworks (python, pytorch, tensorflow, dask, AWS). We impact production directly but also the machine learning … and train models on state-of-the-art GPUs Your work will impact products used by dozens of millions of users worldwide You will be mentored by a senior machine learning scientist to make sure you are successful in your mission You will have the opportunity to publish and open-source your work You will be part of More ❯

/Chief Scientist (Computer Science & Artificial Intelligence) Employment Type: Full-time/Part-time Key Responsibilities Conduct cutting-edge research and drive applications in areas such as Artificial Intelligence, Machine Learning, Big Data Analytics, Computer Vision, Natural Language Processing, and Intelligent Systems Architecture; Lead the application and execution of national or provincial research projects, and promote the commercialization … one major programming language (Python, Java, C++, Go, etc.) with a solid foundation in data structures and algorithms; In-depth understanding of core algorithms and engineering implementation in AI, Machine Learning, or Computer Vision; Familiarity with large-scale computing platforms, distributed systems, cloud architectures, and related toolchains; Proven experience in translating research into industrial applications. Core Competencies: Strategic More ❯

/Chief Scientist (Computer Science & Artificial Intelligence) Employment Type: Full-time/Part-time Key Responsibilities Conduct cutting-edge research and drive applications in areas such as Artificial Intelligence, Machine Learning, Big Data Analytics, Computer Vision, Natural Language Processing, and Intelligent Systems Architecture; Lead the application and execution of national or provincial research projects, and promote the commercialization … one major programming language (Python, Java, C++, Go, etc.) with a solid foundation in data structures and algorithms; In-depth understanding of core algorithms and engineering implementation in AI, Machine Learning, or Computer Vision; Familiarity with large-scale computing platforms, distributed systems, cloud architectures, and related toolchains; Proven experience in translating research into industrial applications. Core Competencies: Strategic More ❯

About the Company We’re working with a next-generation private markets firm that is redefining value creation by combining deep industry expertise with data science and machine learning. This is a unique opportunity to join a company that partners directly with portfolio companies to drive measurable operational and financial performance. They’re now hiring a Lead/Principal … Data Scientist to lead machine learning projects across a wide variety of real-world domains. Working closely with a multidisciplinary team, you’ll have the autonomy to shape technical approaches while staying closely tied to commercial outcomes. This role is ideal for someone who enjoys solving complex, ambiguous business problems using data science, and wants to work at … problems into measurable data science solutions that deliver commercial value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Act as a technical lead within project teams More ❯

About the Company We’re working with a next-generation private markets firm that is redefining value creation by combining deep industry expertise with data science and machine learning. This is a unique opportunity to join a company that partners directly with portfolio companies to drive measurable operational and financial performance. They’re now hiring a Lead/Principal … Data Scientist to lead machine learning projects across a wide variety of real-world domains. Working closely with a multidisciplinary team, you’ll have the autonomy to shape technical approaches while staying closely tied to commercial outcomes. This role is ideal for someone who enjoys solving complex, ambiguous business problems using data science, and wants to work at … problems into measurable data science solutions that deliver commercial value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Act as a technical lead within project teams More ❯

You’ll collaborate with cross-functional teams to design, build, and implement data science solutions that directly feed into core product offerings. This is an exciting opportunity to apply ML and statistical techniques to real-world problems, while also developing in areas such as software engineering, data pipelines, and ethical product delivery. Key Responsibilities Collaborate with product teams to identify … opportunities for ML and data science integration Build and maintain data pipelines to support experimentation and model development Develop and deploy machine learning models in production environments Present insights and results to technical and non-technical stakeholders Apply statistical methods and model validation techniques to reach accurate conclusions Work with data engineers to ensure clean, usable datasets Contribute … research new methods, and continually build your technical capability What We’re Looking For Proficiency in Python or similar languages for scripting and model building Hands-on experience with machine learning, model deployment, and performance evaluation Strong communication skills – able to simplify complex ideas for various audiences Awareness of Agile methodologies and collaborative software development practices A self More ❯

You’ll collaborate with cross-functional teams to design, build, and implement data science solutions that directly feed into core product offerings. This is an exciting opportunity to apply ML and statistical techniques to real-world problems, while also developing in areas such as software engineering, data pipelines, and ethical product delivery. Key Responsibilities Collaborate with product teams to identify … opportunities for ML and data science integration Build and maintain data pipelines to support experimentation and model development Develop and deploy machine learning models in production environments Present insights and results to technical and non-technical stakeholders Apply statistical methods and model validation techniques to reach accurate conclusions Work with data engineers to ensure clean, usable datasets Contribute … research new methods, and continually build your technical capability What We’re Looking For Proficiency in Python or similar languages for scripting and model building Hands-on experience with machine learning, model deployment, and performance evaluation Strong communication skills – able to simplify complex ideas for various audiences Awareness of Agile methodologies and collaborative software development practices A self More ❯

partners directly with portfolio companies to drive measurable operational and financial performance—powered by data. They’re now hiring a Lead Data Scientist to lead high-impact analytics and machine learning projects across a wide variety of real-world domains. Working closely with a multidisciplinary team, you’ll have the autonomy to shape technical approaches while staying closely … problems into measurable data science solutions that deliver commercial value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance … design choices Communicate findings and strategic insights to both technical and non-technical stakeholders About You You’re an experienced data scientist with a proven track record of using machine learning to solve real-world business challenges. You’re just as comfortable in Python as you are in a boardroom, and you’re motivated by measurable impact, not More ❯

partners directly with portfolio companies to drive measurable operational and financial performance—powered by data. They’re now hiring a Lead Data Scientist to lead high-impact analytics and machine learning projects across a wide variety of real-world domains. Working closely with a multidisciplinary team, you’ll have the autonomy to shape technical approaches while staying closely … problems into measurable data science solutions that deliver commercial value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance … design choices Communicate findings and strategic insights to both technical and non-technical stakeholders About You You’re an experienced data scientist with a proven track record of using machine learning to solve real-world business challenges. You’re just as comfortable in Python as you are in a boardroom, and you’re motivated by measurable impact, not More ❯