Top Python Jobs in London

The Senior Backend Engineer will develop backend features for an AI product in healthcare, focusing on systems architecture, data storage, and API integration, while ensuring code quality and scalability.

Lead design and delivery of Google Cloud solutions, set architecture direction, own DevSecOps practices, engage with clients, coach teams, and provide technical account management across cloud projects.

Design and train machine learning solutions for digital identities, focusing on areas like deepfake detection and document understanding, while collaborating with product and engineering teams.

The role involves managing data quality for portfolio risk analytics, troubleshooting data issues, and collaborating with teams to enhance data processes. It requires strong analytical skills and experience in financial data, risk models, and technical proficiency in relevant programming languages.

The Research Analyst will support the International Arbitration team by conducting data analysis, modeling, and reviewing literature to solve complex economic issues related to disputes.

The Senior Data Scientist will collaborate with product teams, develop metrics, design data pipelines, and influence product strategy through data analysis at Intercom.

As a Senior Data Scientist at Intercom, you'll analyze data to drive decisions, support product teams, build data pipelines, and influence product strategy using AI tools.

Design, implement, and maintain data lakehouse architectures on AWS; build secure data pipelines with PII protections and compliance; advise clients across technical and executive stakeholders; manage data residency requirements; collaborate with analytics, security, and legal teams; support ML feature stores and model deployment.

The Full-Stack Engineer will develop core components of a trading system, support production systems, and contribute to trading logic design.

The Software Engineer III (Backend) develops complex software solutions, leads projects, collaborates with teams and creates technical documentation while adhering to best practices.

Lead delivery of advanced analytics and data science for global clients, develop scalable AI-enabled analytics products (prediction engines, experimentation, MMM), embed analytics into client decision-making, and build capability across teams through playbooks and thought leadership.

As a Customer Success Engineer, you will ensure customer adoption of Algolia's search platform through technical onboarding, solution design, and ongoing support, while collaborating with customers and internal teams to drive technical excellence.

Join Starling as a Software Engineer to design, implement, and maintain ML-powered features, collaborating with engineers and data scientists, while delivering impactful solutions in a hybrid working environment.

Lead analytics delivery for high-priority accounts, manage dashboards, execute complex analyses, and mentor team members while enhancing marketing measurement practices.

First-line support for a high-performance research and trading platform: monitor alerts and logs, triage and resolve infrastructure incidents, handle onboarding and environment requests, maintain runbooks, improve monitoring and automation, escalate complex issues, and participate in on-call rotation to ensure platform reliability and responsiveness.

Develop and enhance low latency market data systems using high-performance C++ in a collaborative team environment, contributing to architecture and project leadership.

Support customer-facing AI initiatives by helping discover use cases, build demos and prototypes, configure and test conversational AI experiences, assist integrations with APIs and data sources, participate in workshops and presentations, and document outcomes while learning LLMs, RAG, and prompt design.

As a Software Engineer in Data and Lifecycle, you'll design and implement solutions for trade automations, maintain reference data, and collaborate with stakeholders.

Seeking a Software Engineer for the Data and Lifecycle team to automate trade processes, maintain reference data, and collaborate with stakeholders on derivatives.

Design, build, and deploy AI-powered solutions (LLMs, RAG, agents) to improve productivity and operational efficiency. Partner with business teams to define use cases, integrate AI with enterprise systems, create production-ready prototypes, and ensure solutions meet governance, security, and responsible AI standards.

Lead development and scaling of an enterprise generative AI platform. Work across backend, frontend, and ML/LLM integrations, own major product areas, deliver high-velocity experiments, and ensure scalability and reliability from concept through production.

Customer-facing, hands-on engineer who designs, builds, and productionizes end-to-end data and AI solutions on Databricks. Leads architecture, implements data pipelines and ML integrations, delivers measurable outcomes, and creates reusable assets while working with cross-functional teams and enterprise customers.

Lead cloud network reliability and automation across AWS: design and maintain IaC (Terraform), CI/CD pipelines, load balancers, CloudFront and Cloud WAN, implement observability and governance, participate in incident rotation, and drive cross-functional infrastructure improvements.

Lead system integration, verification, validation and qualification for rail solutions. Develop test plans, execute test specifications, automate testing, manage defects, support stakeholders, and oversee IVVQ tools and configuration control across projects.

Handle complex, custom client requests by building end-to-end reports, performing quantitative analysis and data mining using SQL/pySpark and Python, developing research tools on Similarweb raw data, and partnering with Engineering and Advisory teams to scale solutions and deliver strategic data products.