Work with Python, SQL, JavaScript/TypeScript, NumPy, Pandas/Polars, visualization libraries, and deep learning frameworks (PyTorch, JAX, or TensorFlow) to design and deploy full-stack data-driven applications and machine learning solutions. You will be embedded with Arsenal's Men’s First Team Analysis department, building tools that directly support coaching and analysis workflows.

You will work with kdb+, q, Python or Java, APIs (REST, messaging), Linux, AWS/GCP, Docker/Podman, and CI/CD. You will develop, test and maintain kdb+ applications and supporting services for market data and analytics on a Client Engineering team for a FinTech leader. You will also mentor junior developers.

You'll work with Python, LLMs, Generative AI, RAG architectures, Agentic AI, Conversational AI, Voice AI, Speech-to-Text and Text-to-Speech technologies. This role designs, builds and deploys AI-powered customer and business solutions across Conversational AI, Agentic AI, Voice AI and intelligent automation for a leading international consumer technology and digital services organisation.

You will develop and deploy LLM-powered applications using PyTorch, SGLang, and PEFT/LoRA, building and fine-tuning embedding and reranking models. You will work on an early-stage platform that combines machine learning with real-world trading workflows to transform specialised financial markets. You will join a small engineering team with direct collaboration alongside founders and traders.

Develop agentic AI applications with Python, LLMs (OpenAI, Anthropic), and frameworks like LangGraph or CrewAI, building REST APIs and integrating cloud services (AWS, Azure, GCP). This contract role involves AI solutions for a client in financial services, working with structured financial data and collaborating with product and engineering teams.

Senior Software Developer role in the Data team of a global energy trading house, working on data-consumption and publishing platforms using C#, .NET, ASP.NET, Angular, SQL Server, Oracle, Docker, Grafana, Kafka, Azure Service Bus, and Azure DevOps. Responsible for end-to-end delivery, mentoring, and architectural direction.

Senior Machine Learning Engineer building production AI systems that help UK consumers find financial products. You'll use Python, MLflow, Kubernetes, Databricks, Airflow, LangChain/LangGraph, Terraform, and CI/CD pipelines to design and deploy batch and real-time ML models, LLM-powered capabilities, and monitoring tooling. You'll work closely with data scientists, engineers, and product teams to productionise experimental models and evolve the internal ML platform.

Wise★3.5 (42)· London

You will build scalable systems for business onboarding and verification using Java or JVM languages, Spring framework, JDBC, and relational/non-relational databases with CI/CD pipelines and distributed systems. This engineering team owns end-to-end projects to automate verification, create flexible onboarding journeys, and manage compliance risks for Wise’s money-moving platform across Europe and the UK.

You will work with Python, SQL, BM25, vector search, reranking, RAG, and agentic systems to own and evolve Corestream, Kharon’s risk intelligence feed that surfaces entity-level insights and risk narratives for customers in global security, sanctions, and financial crimes.

Python, SQL, BM25, vector search, reranking, and RAG pipelines powering agentic systems. You will own and evolve Corestream, Kharon’s risk intelligence feed, redesigning semantic search and narrative generation for global-security insights.

Build and deploy AI agents for geopolitical and financial risk intelligence, working with Python, SQL, RAG pipelines, BM25, vector/hybrid retrieval, APIs, Docker, Kubernetes, GitHub Actions, and AWS services like RDS, EKS, and S3. Kharon provides risk-analysis tools for global financial institutions and multinationals, covering sanctions, export controls, and threat identification.

Chubb Insurance★3.7 (1.3k)· London

You will use Python, Hugging Face Transformers, LangChain, LlamaIndex, PyTorch, TensorFlow, Docker, and cloud platforms to build and deploy LLM, RAG, and conversational AI applications. As part of Chubb Insurance's Global Analytics team, you'll design production-ready AI solutions for business value.

You'll work with Java/JVM and Spring on the backend, React/JavaScript/TypeScript on the frontend, plus CI/CD, distributed systems, and relational/non-relational databases. You'll join Wise's Account Integrity team, building fraud-prevention and financial-crime detection systems to protect customer accounts. Wise is a global technology company for moving and managing money.

Tesco★3.5 (25k)· London

You will work with Java, Spring Boot, Kafka, Apache Flink, Apache Beam, NoSQL databases, Redis, and Apache Camel. The Tesco Personalisation team builds real-time, low-latency services for recommendations, offers, and experimentation across web, mobile, and in-store channels using streaming data and ML.

Working with Python, SQL, BM25, vector search, reranking, RAG pipelines, and agentic systems. You will own Kharon's risk intelligence feed Corestream, redesigning its semantic search and integrating graph-based risk outputs into the search layer.

This senior software engineer role uses Python, Snowflake, dbt, Kafka, Java, AWS, and Linux/Docker. You will build ELT pipelines and a streaming platform for tick data, consolidating legacy systems as part of the data engineering team for a systematic hedge fund.

Use Python, SQL, BM25, vector search, reranking, and RAG pipelines to evolve Kharon's Corestream risk intelligence feed—a platform surfacing entity-level insights and topic-based risk narratives, integrating graph-based outputs into semantic search and narrative generation.

Lead a team of Data Scientists and ML Engineers building AI solutions for financial markets using LLMs, Generative AI, Deep Learning, Transformers, Agentic AI, Python, PyTorch, TensorFlow, Hugging Face, LangChain, Semantic Kernel, Azure AI Foundry, AWS AI Services, and MLOps/LLMOps practices.

You will build AI agents using Python, SQL, Docker, Kubernetes, AWS (RDS, EKS, S3), GitHub Actions, RAG pipelines, BM25, vector search, hybrid retrieval, and knowledge graphs. These agents interpret geopolitical and financial signals for Kharon, a company providing global security risk intelligence.

Work with Python, SQL, BM25, vector search, reranking, RAG pipelines, agentic systems, and graph-aware search. Own and evolve Corestream, Kharon’s risk intelligence feed that surfaces entity-level insights and topic-based risk narratives for global security clients.

Work with Python, LLMs, RAG pipelines, vector databases, Hugging Face Transformers, LangChain, PyTorch, and Docker to build production AI systems. Design, develop, and deploy AI-powered solutions such as conversational AI, document intelligence, and backend services for the Global Analytics team.

You'll use Java, Kafka, Flink, SingleStore, HDFS/S3, and Scala to build high-performance, low-latency data systems. The Data Platform team in Global Markets owns the post-trade stack, processing high volumes of data and developing an AI-powered analytics UI/agent framework.

Work with Java/Spring, React, JavaScript/TypeScript, CI/CD pipelines, and distributed systems. You'll join the Account Integrity team building a globally scalable fraud prevention engine to protect customer accounts and prevent financial crime using machine learning and real-time monitoring.

You'll use Python, SQL, shell scripting, containerization, infrastructure-as-code tools, and Scala/Java or Python to build and maintain scalable data pipelines. You'll support a financial technology company's data infrastructure, contributing to AI/ML experiences and international applications. No team size is stated.

Lead a team of ML engineers building production systems—real-time inference APIs, batch data products, and LLM-based agentic solutions—for Compare the Market’s AI platform. You’ll set technical direction using Python, Terraform, GitHub Actions, ArgoCD, and frameworks like LangGraph/LangChain, ensuring robust, scalable, and observable systems.