1 to 25 of 91 Algorithms Jobs in London

Analysis & Modelling Conduct in-depth exploratory data analysis to identify trends, patterns, and anomalies across diverse datasets. Develop and deploy predictive models, machine learning algorithms, and statistical techniques, including natural language processing (NLP). Perform quantitative analysis to support scenario testing, stress testing, and thematic risk assessments. Ensure models ...

stakeholder reporting. Analyse large volumes of structured and unstructured data from diverse sources to identify patterns, anomalies, and potential risks. Develop analytical models and algorithms to support fraud detection, financial crime monitoring, misconduct investigations, and regulatory compliance initiatives. Apply advanced analytical techniques to detect suspicious transactions, behavioural patterns, and emerging ...

design and deliver production systems that enable systematic trading at scale. You partner with researchers and traders to translate ideas into resilient, performant algorithms and execution platforms. You thrive in a dynamic, collaborative environment and bring a builder’s mindset to continuously improve models, tooling and workflows. Job Responsibilities Design ...

developing production quality Python is essential Deep understanding of Agentic AI systems and multi-agent architectures Proficiency in machine learning and and deep learning algorithms such as Deep learning, NLP, Neural networks, multi-class classifications, decision trees, support vector machines, Strong adherence to software and ML development fundamentals (e.g. code ...

/AI for quant finance (signal extraction, surrogate modeling, anomaly detection), including MLOps, drift monitoring, and explainability. Knowledge of portfolio optimization, hedging algorithms, execution analytics, and transaction cost modeling. Familiarity with distributed computing and market data tooling (e.g., kdb+/q, SQL), and performance engineering for large-scale simulations. Contributions ...

pipelines. Review code, mentor teammates, and promote engineering best practices. Profile The Backend Developer will have strong software engineering fundamentals, including data structures, algorithms, and system design. Professional experience building and operating backend applications in production environments. Proficiency in at least two or morebackend programming languages such as: Python ...

/AI for quant finance (signal extraction, surrogate modelling, anomaly detection), including MLOps, drift monitoring, and explainability. Knowledge of portfolio optimisation, hedging algorithms, execution analytics, and transaction cost modelling. Familiarity with distributed computing and market data tooling (e.g., kdb+/q, SQL), and performance engineering for large‐scale simulations. Contributions ...

/CD driven application deployments. Consult science users on application scalability to PBs of data by having a deep understanding of software engineering, algorithms, and underlying hardware infrastructure and their impact on performance. Confidently optimizes design and execution of complex solutions within large-scale distributed computing environments Produces well-engineered ...

with a track record of taking models from prototype to production in large, complex environments. Technical depth across modern AI. Deep expertise in ML algorithms, neural networks, large‐scale architectures, and modern frameworks. Hands‐on experience with Generative AI, Agentic AI, LLMs, foundation models, and large‐scale inference. Strong engineering ...

improving outcomes for clients and the firm, this role was built for you. Responsibilities Execution Algorithm Design & Development Design, implement, and maintain production execution algorithms from scheduling models to adaptive allocation strategies driven by real‐time signals and analytics. Build and enhance and optimize venue selection, queue priority modelling ...

product partners and stakeholders to identify opportunities to apply AI/ML to content, data, and products • Conduct research and identify AI/ML algorithms and methods to solve specific business problems • Implement rigorous testing and evaluation of potential solutions; review indicative results and proofof- concepts with multi-disciplinary teams ...

deploying AI solutions in cloud environments. Technical Skills: Proficiency in programming languages such as Python, Java, or C++. Strong understanding of machine learning algorithms, deep learning ...

protocol analysers Strong problem-solving skills and hands-on engineering mindset Desirable Experience Wearable technology development Sports technology products Signal processing Sensor fusion algorithms Python for test automation or data analysis PCB design experience using Altium, KiCad, or similar ECAD tools Manufacturing and product certification experience Experience working in start ...

GenAI applications using LangChain and LangGraph (agent architecture design, state management, and graph-based workflow orchestration). ML & Cloud Ecosystems: Solid understanding of ML algorithms, FastAPI, PyTorch/TensorFlow, MLflow, MLOps practices, containerization (Docker, Kubernetes/AWS EKS), and cloud services (AWS Bedrock, SageMaker, Azure AI Search). Soft Skills ...

grade products. You'll support use cases across DAX, Global's digital ad exchange platform , such as our 'cross - device' audience identity graph and algorithms to deliver real-time targeting across our audience . This role is ideal for someone who combines strong engineering fundamentals with hands-on machine learning ...

robotics and IoT-powered operations The Opportunity As a Software Engineer at Relay, you'll: Own challenging, impactful problems end-to-end, from routing algorithms to real-time optimisation services and intuitive operational tools. Collaborate closely with top engineers, data scientists, and product leaders in a highly autonomous and impact ...

containerisation (Docker, Kubernetes) Experience building data pipelines and working with large datasets (SQL, Spark or similar) Strong understanding of machine learning algorithms and statistical modelling techniques Experience collaborating across data science and engineering teams Machine Learning Engineer, Python, MLOps, model deployment Reasonable Adjustments: Respect and equality are core values ...

skills Flexible approach to hybrid working and occasional travel Nice to have: Degree in Computer Science or related field Strong CS fundamentals (data structures, algorithms, problem solving) Healthcare/HealthTech experience Immediate availability If you're interested in this role, click 'apply now' to forward an up-to-date copy ...

engineering, with a proven track record of shipping production AI systems. Bring deep expertise in NLP, Computer Vision, and/or Multimodal LLM algorithms, with a strong foundation in statistics, optimization, and ML theory. Apply practical experience implementing distributed, multi‐threaded, and scalable applications using frameworks such as Ray, Horovod ...

powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning knowledge into practice with a hands ...

powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning knowledge into practice with a hands ...

powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning knowledge into practice with a hands ...

powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning knowledge into practice with a hands ...

powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine Learning Project Put your machine learning knowledge into practice with a hands ...

monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour Collaborate with data scientists to productionise ML models and forecasting algorithms Your Skills Extensive hands-on professional experience in the field of Artificial Intelligence, Machine Learning, or related engineering domains. End-to-end exposure in model ...