Citi★3.9 (21k)· London

You will work with TypeScript, React, HTML5, CSS, JavaScript (ES6+), Chromium/Electron/OpenFin, FDC3, REST/WebSocket APIs, Kafka/Solace/Tibco, and CI/CD with Jenkins. The team delivers pricing solutions and trading GUIs for Citi’s Foreign Exchange business. You will provide technical leadership, mentor junior engineers, and drive AI integration.

You will work with OpenMM, OpenFE, molecular dynamics, MM/GBSA, free-energy perturbation (RBFE/ABFE), and GPU infrastructure to define and validate automated biophysics tools. The team builds a scalable platform for agentic drug discovery workflows, ensuring scientific correctness in molecular simulation.

This role involves working with Python, PyTorch, JAX, CUDA, Linux, Docker, Kubernetes, Slurm, Ray, Flyte, and Argo. The team builds ML and physics-based infrastructure for drug discovery, including simulation workflows and agent-usable scientific pipelines. Engineers improve code quality, GPU efficiency, and distributed execution while making research tools scalable and maintainable.

You will lead AI and automation initiatives using n8n, Claude, Zapier, and API integrations. As a product leader at a London-based eCommerce and paid media consultancy, you will drive efficiency across teams by automating workflows and building internal AI-powered tools. You will manage a small team of automation specialists or developers.

Bloomberg★3.8 (1.1k)· London

Define strategy for AI Platform Experiences & Integrations within Bloomberg’s CTO Office. Work with UX and engineering teams on generative AI, agent systems, and emerging interfaces (MCP, A2A, A2UI). Product teams interact with these platforms through agent-driven experiences, copilots, and workflow orchestration surfaces.

You'll work with 5G/6G, machine learning, large AI models, LLMs, and AIGC to develop a wireless network digital twin system for smart city logistics and last-mile applications, including performance analysis, radio propagation modelling, and network optimisation for EU/UK projects.

Work with TensorFlow or PyTorch, Python, and related computer vision/graphics libraries on neural network architectures (convolutional, recurrent, transformer, diffusion-based). The Visual Computing Group (VCG) researches and develops generative models for game rendering and live video streaming to advance state-of-the-art runtime efficiency, visual quality, and latency.

Use Python, SQL, graph databases, Docker, Kubernetes, and LLMs to own Kharon’s risk-propagation engine that evaluates entities in a knowledge graph and surfaces risk signals. The role spans research, data engineering, and product to evolve a production system for global security analytics.

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 own Relay’s Demand Forecasting models, working hands-on with Python, ML frameworks, and forecasting tools to predict parcel volume, weight, and size at outcode granularity out to D30. You set the technical direction for the Network squad’s forecasting engine, which drives sortation, middle-mile, last-mile, and expansion decisions. The centralised data team has ~30 people, with you acting as the senior IC anchor, mentoring a Senior Data Scientist and an Analyst.

You'll work with TypeScript, React, SQL, Amplitude, GrowthBook, PostHog, LaunchDarkly or Statsig, and Customer.io or Braze. The company is building a senior AI employee for small-business owners that drafts client work from existing tools. You own the activation funnel, experiment framework and retention loops as the first growth engineer on a small senior team.

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.

Build features across a dual-stack backend (TypeScript, C#, .NET) and microfrontend React apps, using AWS (ECS, Lambda, SQS, DynamoDB, DocumentDB), Terraform, SST, and AI coding agents. You'll evolve a B2B SaaS platform that powers UK housing transactions, adding new AI capabilities alongside a mature .NET foundation.

Lead UI Developer role using TypeScript, React, RxJS, WebSockets/SSE, GraphQL, Protobuf, Flatbuffers, Jest/Vitest, React Testing Library, Playwright, and AG Grid. You will own the front-end architecture for a real-time Single Dealer Platform used by Sales, Trading, and institutional clients globally, building low-latency trading applications for market data, pricing, RFQ, and trade capture.

Lead Software Engineer for the PRIIP Cloud platform, owning full-stack development with TypeScript/Node.js, React, Java/Kotlin, REST APIs, event-driven architectures, AWS, Docker, and Kubernetes. The team builds a cloud-based PRIIP documentation and reporting system for regulated financial services, collaborating with compliance, quant, and product specialists. This role leads a multidisciplinary team of engineers and subject matter experts.

Develop backend services using Node.js, Python, Java, C#, PHP, and Ruby on Rails, with databases including MySQL,

TypeScript, React, Node.js, Bun, Kubernetes, and AWS. The team builds web apps, back-office systems, and tooling for financial product comparison across money.co.uk, Uswitch, and Confused. As a Staff Software Engineer, you set technical direction for Financial Services.

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.

Design, build, and operate a Kubernetes-based MLOps platform using Helm, Terraform, Kubeflow, KServe, vLLM, and JupyterHub. The platform supports the full model lifecycle—experimentation, deployment, and scalable inference—for AI, ML, and LLM workloads in production.

You'll build and operate a Kubernetes-based AI/ML platform using Helm, Terraform, Kubeflow, KServe, vLLM, and JupyterHub. This role focuses on creating infrastructure, tooling, and guardrails so MLOps and data science teams can reliably deploy and serve models at scale.

You’ll build cloud-native applications for a leading global financial institution, using Java with Spring Boot and React to support critical financial operations.

You will work with backend development, databases, APIs, cloud services and production machine learning systems. This is for a growing technology business. No specific project or team size is mentioned.

Monzo★3.5 (108)· London

You will build and deploy deep learning, graph-based, and sequence-based ML models using Python and SQL, with exposure to Go. You will design human-in-the-loop systems and autonomous agents to route, prioritise, and automate customer-support issues for millions of customers across thousands of support staff at Monzo. You will be one of four ML engineers embedded in product squads.