1 to 25 of 72 Permanent Algorithms Jobs in London

knowledge of CI/CD, testing and deployment You have a thorough understanding of Computer Science fundamentals such as OOP, Data Structures, Design Patterns, Algorithms You're collaborative and pragmatic with great communication skills You're degree educated in a STEM discipline, having achieved a 2.1 or above What ...

reliability Collaborate with cross-functional teams and stakeholders Ensure compliance with banking regulations and security standards Your Skills: Strong Python programming Expertise in ML algorithms and statistical modeling Hands-on experience with Scikit-learn, Pandas, NumPy, XGBoost/LightGBM Experience with TensorFlow/PyTorch/Keras Solid understanding of feature ...

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 ...

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 ...

trading technology Experience: Degree in Computer Science, Engineering, Mathematics, Physics or similar quantitative discipline Strong Java fundamentals Exposure to Python Understanding of data structures, algorithms, networking fundamentals, OOP and software design patterns Familiarity with Linux/Unix environments Git or similar version control systems Nice-to-have: Financial markets ...

trading technology Experience: Degree in Computer Science, Engineering, Mathematics, Physics or similar quantitative discipline Strong Java fundamentals Exposure to Python Understanding of data structures, algorithms, networking fundamentals, OOP and software design patterns Familiarity with Linux/Unix environments Git or similar version control systems Nice-to-have: Financial markets ...

Strong Java, Python, microservices, REST APIs, distributed systems. RDBMS (Oracle/SQL Server/Postgres), CI/CD, Docker, Kubernetes. JVM tuning, performance optimisation, algorithms & data structures. L3 production support experience. Experience with LLMs, AWS, LangChain/LangGraph, and agentic AI frameworks. Desirable: Mentoring/technical leadership. Financial services experience. ...

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 ...

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 ...

standards around testing, code quality, and reliability Core Technical Requirements Strong professional experience with modern C++ (C++17/20) Deep understanding of data structures, algorithms, and low-level system behaviour Experience working on latency-sensitive or performance-critical systems Strong knowledge of Linux, memory management, and concurrency Comfortable debugging complex ...

related technical discipline from a leading university. Strong commercial experience as a C++ Developer with deep expertise in modern C++ , software engineering principles , algorithms , and data structures . Experience developing high-performance systems , low-latency applications , backend platforms , or scalable infrastructure using C++ . Strong understanding of systems programming , multithreading ...

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 ...

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 ...

quantitative or technical field (e.g. Computer Science, AI, Mathematics, Statistics, Physics, Engineering) Strong Python skills with experience building machine learning models and scalable algorithms Proven experience working with large, complex datasets to optimise performance and decision-making Commercial experience applying data science in real-world environments , ideally within fast-paced ...

very well be the right place for you. The Quantitative Analytics team at Centrica Energy is part of the Trading Analytics and Algorithms centre of excellence, and is responsible for: Delivering quantitative analysis of complex and structured products, that provides insight to help traders to maximise value and manage risk ...

ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured ...

/or C++ , depending on background) Experience building tools for quant research, systematic strategies, or data-driven trading Solid understanding of data structures, algorithms, and software engineering best practices Familiarity with market data, time-series analysis, or trading system design Ability to work independently while collaborating closely with a small ...

Exceptional programming skills in Python and/or C++, with a focus on writing clean, performant production code Strong understanding of core CS fundamentals (algorithms, distributed systems, profiling, testing) Experience in a systematic trading environment or quantitative data domain is highly advantageous, though not essential A problem-solver with ...

Golang developmen t.Strong understanding of Go routines, channels, concurrency, and memory managemen t.Experience building REST APIs and microservice s.Strong knowledge of data structures, algorithms, and software design principle s.Experience with SQL databases such as PostgreSQL, MySQL, or Oracl e.Experience with NoSQL databases such as MongoDB, Redis, or Cassandr a.Knowledge ...