JPMorgan★3.9 (20k)· London

Principal Data Engineer at JPMorganChase, working with SQL, Python, Spark, cloud platforms, Databricks, Apache Iceberg, and distributed frameworks like Hadoop and Kafka. The role designs and builds scalable data warehouse solutions, data pipelines, and ETL processes for the firm’s portfolios. Mentors junior engineers and partners with architects on delivery roadmaps.

You will work with Python, Go, or PowerShell; REST APIs for Slack, Google Workspace, and Okta; SaaS security tools like AppOmni or Adaptive Shield; and Google/Atlassian stacks, IAM, DLP, and data governance systems. You will safeguard corporate identity systems, sensitive data, and physical workspaces for a team advancing AI-driven drug discovery.

LSEG★3.7 (403)· London

Work with Azure, AWS, Terraform, Bicep, CloudFormation, Ansible, Docker, Kubernetes, Python, Bash, PowerShell, Go, CI/CD, and generative AI tools. Build scalable AI products and platforms by owning cloud infrastructure, delivery pipelines, and operational engineering. This individual contributor role provides functional leadership, guiding engineers without direct reports.

WTW★3.6 (1.7k)· London

This role shapes WTW’s enterprise-wide AI engineering capability, defining technical direction for production-grade generative AI and agentic systems. You will work with Microsoft Foundry, Copilot Studio, Lyzr, Anthropic Claude, Moveworks, LLM/agent frameworks, and Model Context Protocol while building RAG pipelines, LLMOps practices, and governed integration patterns.

Wise★3.5 (42)· London

Work with Python, big data tools like Hadoop or Spark, and cloud platforms such as AWS, GCP, or Azure, collaborating with engineers on the Treasury team. Build and refine models to forecast and manage liquidity, balancing sufficiency and risk for Wise’s multi-region money movement products.

The API Platform team owns Perplexity's public-facing surface: the Search API, Agent API, SDKs, and docs. Engineers work in Go, Rust, and Python across cloud infrastructure, Kubernetes, and CI/CD, building agent-consumed surfaces like hosted MCP, tool calling, and auth flows while owning APIs end to end from RFC to production.

Wise★3.5 (42)· London

You’ll use Python, SQL, predictive ML models, recommendation systems, and A/B testing to own production-level model pipelines. Wise is a global fintech moving money across borders. In this IC role on the CRM Tribe, you’ll develop learning systems that recommend the right product to the right customer at the right moment.

Ebury★3.3 (13)· London

Senior Software Engineer (Money Flows) at Ebury (London, hybrid) will work with Python, Django, FastAPI, PostgreSQL, Kafka, AWS, Kubernetes, Terraform, Jenkins, Prometheus, and Kibana. The role owns development, scalability and optimisation of the company’s multi-currency account systems, incoming funds, and outgoing payment processes on its core transactional platform. This is a global team spanning Europe and South America.

Hudson River Trading★4.5 (2)· London

You will work with macOS, Apple Business, MDM (Jamf, Workspace One, Intune), AutoPkg, Munki, Bash/Python, and enterprise networking. As an endpoint engineer on Hudson River Trading’s Enterprise Technology team, you will solve macOS challenges and improve user experience across the firm, which builds sophisticated computing environments for algorithmic trading.

Wise★3.5 (42)· London

A Lead Data Scientist will work with Python, SQL, and machine learning models (classification, propensity, churn, next-best-action) using gradient boosting, neural networks, or linear models. They will design data pipelines and ML infrastructure for Wise’s Marketing CRM team, building recommendation systems to personalize customer communications. This individual-contributor role involves developing production models, running A/B tests, and influencing product strategy.

Citi★3.9 (21k)· London

You will work with C++, C#, .NET, Java, Python, kdb, and SQL to develop analytics libraries and pricing models using Monte Carlo methods and PDE solvers. The role focuses on creating quantitative models for Citi’s cross-asset XVA and capital analytics, supporting trading business pricing and risk-management. You will collaborate with Traders, Structurers, and technology professionals.

Faculty★0.0 (16)· London

Research Scientists execute technical research in AI safety, using Python with PyTorch to study and steer transformer-based LLMs via white-box and black-box interpretability techniques like mechanistic interpretability and steering vectors. They collaborate with senior scientists at Faculty, a company that builds and deploys human-centric AI for over 350 global clients.

You'll use Zapier, Make, n8n, Python or JavaScript, APIs, SQL, and webhooks. You'll own the automation layer for influencer marketing, building workflows for discovery, onboarding, contracts, content tracking, reporting, and payments.