1 to 25 of 72 Permanent Algorithms Jobs in London

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 ...

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 ...

/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 ...

/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 ...

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 ...

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 ...

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 ...

prefer candidates with a degree in Computer Science or a related field. We prefer candidates with strong computer science fundamentals, including data structures, algorithms, and problem solving. We prefer healthcare or healthtech experience. We prefer immediate availability. We need a flexible approach to hybrid working and occasional travel. Responsibilities ...

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 ...

integrate data science models seamlessly into our tech stack. Experimentation & Insights Design and execute rigorous A/B tests to validate new features, algorithms, and product iterations. Apply advanced statistical and probability theory to evaluate model performance and user behavior. Utilise our extensive data infrastructure to uncover insights that drive ...

Oracle) You're comfortable with JavaScript/React You have a thorough knowledge of Computer Science fundamentals such as OOP, Design Patterns, Data Structures, Algorithms You are collaborative with excellent communication and stakeholder management skills You are degree educated in Computer Science or similar technical discipline Apply now to find ...

quantitative research methodologies. Requirements • Technical Skills: Strong programming skills in C#/.NET with a solid grasp of computer science fundamentals (data structures, algorithms, and design patterns). • Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Engineering, or a related quantitative field. • Mindset: An analytical mindset with ...

management, options trading and trading analytics. The successful candidate will contribute to all areas of the trading platform, including risk calculations, volatility models, execution algorithms, research tooling and infrastructure. This is a highly technical role in a fast-moving environment where engineering quality, performance and latency have a direct impact ...

management, options trading and trading analytics. The successful candidate will contribute to all areas of the trading platform, including risk calculations, volatility models, execution algorithms, research tooling and infrastructure. This is a highly technical role in a fast-moving environment where engineering quality, performance and latency have a direct impact ...

experiments on the latest deep‐learning techniques (sparsified 70 B + runs, distributed training on thousands of GPUs). Design, implement and benchmark ML algorithms; write clear, efficient code in Python. Deliver prototypes that become production‐grade components for Le Chat and our enterprise API. About you Master ...

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 ...