1 to 25 of 209 Machine Learning Jobs in the City of London

been removed by the job board, full contact details are readily available on our website). Keywords: Machine Learning Researcher/ML Research Scientist/Applied Machine Learning Scientist/AI Researcher/Research Engineer/Machine Learning Engineer/AI Engineer/Applied … Engineer/ML Scientist/Deep Learning Researcher/NLP Researcher/Research Software Engineer/Python/PyTorch/Large Language Models/LLM/LangChain/LangGraph/AI Agents/Enterprise Search/Neural Networks/Model Deployment/Edge AI/TensorFlow/scikit-learn ...

Graduate Machine Learning Researcher at IMC, your work will directly impact our global trading strategies. You will apply advanced machine learning, statistical, and computational techniques to solve complex, real-world trading problems, contributing to trading strategies across global equities, futures, and options markets. Machine Learning … Electrical Engineering, Mathematics, Statistics, Physics or a related quantitative field Strong foundations in machine learning, probability, and statistics, with experience applying advanced ML techniques to solve challenging research or real-world problems Demonstrated hands-on research experience in deep learning fundamentals such as neural network architectures, sequence ...

partners to develop your career and the solutions we deliver for our clients. In this role you will: Solve challenging business problems using advanced machine learning methods such as Deep Learning and quantitative analytics. Understand business requirements and support the development of business cases. Run discovery analytics … identify new and innovative opportunities. Partner with developers and engineers to deploy machine learning algorithms to deliver business value. Define approaches to embed and scale machine learning models. Build reusable assets, solutions and develop best practices for current and future business problems. Consult on complex analyses ...

Lead Applied Scientist - AI & Machine Learning London (Hybrid - 2-3 Days per Week in the Office) Salary: £95,000 - £120,000 + Bonus + Excellent Benefits Are you an experienced AI and Data Science leader looking to shape the future of Generative AI and Machine Learning … challenges. The Opportunity As the senior scientific authority within the AI and Data Science function, you will lead the development of innovative AI and ML solutions from concept through to production. You'll work closely with engineering, business stakeholders, and senior leadership to ensure solutions are robust, scalable, and deliver ...

Would you thrive in a fast-scaling business, solving novel problems in collaborative teams? Are you interested in developing machine learning models for difficult green-field problems? If so, you could be the person we are searching for. We are an IoT innovator working to scale our product … developing technology that will change paradigms, contribute to a sustainable future, and improve lives. We are building Virtual Energy Infrastructure using our world-leading machine learning algorithms. We’re looking for a Machine Learning Research Engineer to work with us in our Data Science ...

learning, AI, and want to contribute to the platform capability development for our whole organization, we invite you to apply. Responsibilities Design the ML deploy, monitoring pipelines and engineering infrastructure to support enterprise machine learning systems at scale Take offline models data scientists build and turn them … years of experience in AWS & Terraform, Jenkins, Cloudformation or any other IAAC. Proven Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer on AWS Sagemaker and similar tools. Knowledge and experience with CI/CD tools. Strong hands-on technical skills in automation (Jenkins, GitLab, Docker ...

Machine Learning and AI. About the Role To strengthen our AI for Science (AI4S) team, we are looking for AI/ML Engineers with a track record in developing and validating machine learning models for real-world scientific problems. You will drive the development … development from day one. We strongly encourage applications from people with diverse and underrepresented backgrounds and perspectives. Why you? Design and implement AI/ML-driven solutions throughout the entire model development life cycle. Research and develop state‐of‐the‐art machine learning models and agentic systems ...

engaging closely with both technical and non-technical stakeholders. Delivery is supported by a strong technical assurance and review culture, encouraging challenge, learning and high standards. You will work within security, compliance and governance constraints where quality and judgement matter as much as pace. What You'll Be Doing … learning models Experience evaluating models through quantitative evidence and structured experimentation Strong software engineering practices, producing readable, testable and maintainable code Experience integrating ML solutions into production systems and workflows Feels confident working in secure, regulated or high-assurance environments In Return You'll work on genuinely challenging machine ...

seeking Deep Learning Researchers to join our growing team. As a Deep Learning Researcher, you will develop and apply state-of-the-art deep learning techniques at the intersection of AI and markets. You will help accelerate our efforts in areas such as modern neural network architectures … learning research or applied machine learning. For PhD candidates, we expect a record of research contributions in your area published at leading ML venues (e.g., NeurIPS, ICML, ICLR). For Bachelor’s and Master’s candidates, research experience is required but can take other forms, e.g. thesis work ...

Learning team and take ownership of driving the adoption and implementation of AI across the business. This will include integrating AI/ML capabilities into their core SaaS products, which are used by a range of wealth management firms, banks and FinTech organisations globally. More about the company … 2017. London based - twice a week in the office. Work with some of the largest FinTech & Payments companies globally. Investing heavily in AI/ML to simplify processes and enhance their products. Award-winning business and part of a wider financial services group. The Role - Head of Machine Learning ...

Learning team and take ownership of driving the adoption and implementation of AI across the business. This will include integrating AI/ML capabilities into their core SaaS products, which are used by a range of wealth management firms, banks and FinTech organisations globally. More about the company … 2017. London based - twice a week in the office. Work with some of the largest FinTech & Payments companies globally. Investing heavily in AI/ML to simplify processes and enhance their products. Award-winning business and part of a wider financial services group. The Role - Head of Machine Learning ...

with machine learning techniques. Always with an ethical and accurate lens. A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices. Wherever you land, you’ll be working with … transform how the Bank serves customers and empowers colleagues. Data engineering, MLOps and intelligent automation, creating resilient data pipelines, scalable deployment architectures and automated ML workflows using contemporary engineering and CI/CD practices, enabling AI solutions to operate reliably across the enterprise. AI assurance, evaluation science and model governance ...

years of experience in software engineering, with strong proficiency in C#, Node.JS, Databases (SQL, NoSQL) and 2+ years of experience working with AI/ML technologies, frameworks (e.g., TensorFlow, PyTorch), and developing machine learning models with Python. Strong problem-solving skills and the ability to break down complex … explore new ideas and approaches. Familiarity with MLOps (Machine Learning Operations) practices, including the deployment, monitoring, and maintenance of AI/ML models in production environments and experience with cloud platforms and deploying AI/ML models in production environments. Even if you don’t meet every requirement ...

Help shape how AI is built, deployed, and scaled across JPMorganChase. You will work on business-critical products that apply modern machine learning to software, cybersecurity, and technology infrastructure. You will partner with engineers and research teams to take ideas from prototype to production. If you enjoy solving … architecture. You will help the team deliver trusted, market-leading AI technology products through modern engineering practices. Job Responsibilities Collaborate with data scientists and machine learning engineers to deliver AI products into production Design, develop, deploy, and maintain full stack AI applications and services Build and maintain data ...

production, ensuring the ongoing reliability and stability of our systems. This role offers you the opportunity to lead, deliver, and care for cutting-edge ML systems that impact millions of customers daily. These are some of the key components to the position: Collaborate extensively with Data Scientists, Product Managers … Backend Engineers to bridge the gap between model development and production systems Lead the architectural design of end-to-end ML systems, from data ingestion and training pipelines to real-time inference and monitoring infrastructure Transform innovative data science prototypes into robust, scalable, and secure production software, taking ownership ...

specialists who develop novel AI solutions to mission focussed problems. In this role you will be responsible for the technical development of AI/ML projects, working alongside more senior members of the team, supporting projects from initial idea scoping right through to final project delivery both in customer … team, with some guidance and direction from seniors. Bring experience in developing and delivering data-centric solutions. Undertake research and applied AI/ML tasks on both customer and internal research projects. Work with autonomy on assigned tasks within project groups. Generate ideas for new research directions. Deliver AI/ ...

organization with multiple teams to improve the efficiency of company processes and provide insights and assistance to users. Responsibilities Design, implement, and deploy machine learning models and systems to solve complex problems and drive business outcomes; Research, develop, and implement machine learning algorithms and models … implement AI tools such as NLP, LLM, and IA; Collect, preprocess, and curate large datasets required for training generative models; Experiment with different machine learning techniques and algorithms, including supervised, unsupervised, semi-supervised, reinforcement, and deep learning; Design and optimize machine learning pipelines and workflows ...

Data UK practice, within the AI & Modelling Craft: a community of data scientists, AI engineers, modellers and solution architects focused on applying AI, machine learning and advanced analytics to solve customer and growth challenges. Our teams work across the full lifecycle, from identifying opportunities and designing solutions through … building, deploying and operating AI products that deliver measurable business value. What You Will Do Design and deliver customer analytics, data science, machine learning and generative AI solutions, from problem framing and data exploration through to production and measurable client value. Make the technical decisions on your workstream ...

join their dynamic team on a fixed-term contract basis for 12 months. This is an exceptional opportunity to leverage your expertise in machine learning and statistics to drive impactful data science solutions that enhance customer experiences and optimise business operations. Role Overview: As a Data Scientist … will be at the forefront of developing and deploying machine learning models that directly influence decision-making processes, customer service, and overall business performance. Your work will involve: Designing and implementing robust machine learning models and data pipelines. Experimenting with innovative approaches to translate complex business ...

that drive strategic and operational decision-making. As the first dedicated Data Science role within the organisation, the role will lead the application of machine learning and statistical modelling to solve business challenges, while defining the tools, standards and best practices required to build a scalable Data Science … decision-making. Deliver Data Science solutions across a range of use cases including customer attrition, credit risk, likelihood-to-pay and pricing optimisation. Apply machine learning, statistical and analytical techniques to solve complex business challenges and generate measurable business value. Evaluate and continuously improve model performance through testing ...

/ML Computational Scientist As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third‐party AI services to deliver production‐ready outcomes. Your role spans the full solution lifecycle … include big data, high‐performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks. Experience in building and deploying AI/ML based software to a cloud environment. Strong written & verbal communication skills and ability to communicate complex technical concepts to non‐technical stakeholders. Strong client‐facing skillsets ...

evaluate new internal software releases, provide feedback to software engineering teams, make necessary code fixes, and conduct code reviews. Benchmark models and key ML techniques to identify performance bottlenecks and improve model efficiency. Design and conduct experiments on novel AI methods, implement them and evaluate results. Collaborate with Research, Software … C++ software development skills. Expertise in deep learning from model training to optimisation and evaluation. Experience in distributed training or inference of ML models across 64+ accelerators. Capable of designing, executing and reporting from ML experiments. Developed deep understanding of performance bottlenecks and how to overcome them. Ability ...

Applied Innovation (of AI) Engineering team is an elite machine learning group strategically located within the Chief Data Analytics Office (CDAO) Technology group of JP Morgan Chase. AI Engineering tackle business critical priorities using innovative machine learning techniques and technologies with a focus on machine learning for Software, Cybersecurity and Technology Infrastructure. The team partners closely with all lines of business and engineering teams across the firm to execute long-term projects in these areas that require significant machine learning development to support JPMC businesses as they grow. As a Principal ...

business make it a great place to put cutting-edge AI to use. CFC's Data & AI team is building production agentic and ML systems that automate and inform complex underwriting decisions that drive real business outcomes - not demos, not proof-of-concepts sitting on a shelf. The team includes … ML engineers and software engineers shipping production services, and this role sits alongside them as an analytical counterpart: running experiments, stress-testing assumptions, and generating the evidence that shapes what gets built and how it improves over time. We are looking for a mid-level Data Scientist to join ...

actively working on building a future in which state-of-the-art software, Artificial Intelligence (AI) and Machine Learning (ML) enable us to develop new therapies and personalized medicines that drive better outcomes for patients at reduced cost with fewer side effects. This ambitious mission requires scalable, cloud … models in production with efficient use of compute. Develop and maintain cloud-native architectures that enable reliable deployment and scaling of AI/ML workloads. Deliver robust, tested and high-performance code in an agile environment, and work closely with ML engineers and domain experts to make the infrastructure ...