Top Python Jobs in London

The Research Engineer will develop innovative generative 3D machine learning methods, train and optimize models, and refine 3D content generation processes, focusing on geometric accuracy and integrating physics-aware capabilities.

Build and operate distributed ingestion and processing pipelines, ensure reliability and performance, define data contracts, add observability and testing, improve platform reliability and CI/CD, and participate in design/code reviews and incident retrospectives.

The Internal Audit Manager enhances audit effectiveness via advanced analytics, delivers data insights on risk, and manages audit-related data projects.

Lead product-focused analytics and experimentation to uncover growth opportunities, define KPIs, analyze user behavior and retention, quantify feature impact, and communicate data-driven recommendations to cross-functional stakeholders.

Own availability and performance of mission-critical services, improve scalability and observability, build platform tooling, run on-call rotations, practice blameless incident response, collaborate with product teams, and follow FinOps best practices.

Lead backend architecture and cross-functional projects, build scalable Python/Django services and integrations, mentor engineers, improve performance and observability, and drive data-informed product decisions.

Lead design and evolution of scalable data models and ETL/ELT pipelines, own Looker/LookML BI layer, ensure data quality/governance, collaborate with data science, and drive company-wide analytics strategy.

Partner with Payments Operations to analyze and optimize pay-ins, payouts, and fraud. Build statistical and ML models, design experiments, monitor transaction health, improve risk rules, and deliver insights to shape product and monetization strategy.

Lead design and evolution of core analytical data models, define analytics engineering standards, build and optimize ETL/ELT pipelines, own the BI/semantic layer (Looker/LookML), drive data quality and governance, partner with cross-functional teams, and mentor analytics engineering across the company to enable reliable, scalable decision-making and experimentation.

Work in a cross-functional team to design, build, and own backend features and services (primarily Python/Django), implement A/B tests, ensure monitoring and reliability, troubleshoot production issues, and guide technical decisions to improve quality and scalability.

Lead technical direction across platform squads, ship and operate critical platform services, improve CI/CD and delivery workflows, drive reliability (SLOs, observability, runbooks), remediate production issues, mentor engineers, and participate in on-call and incident response to raise platform quality and developer experience.

As a Data Engineering Intern, you'll build data processing pipelines, support finance teams in decision-making, visualize finance indicators, and drive projects from initiation to production.

The Data Engineer Operations will design automated tools and dashboards to optimize trading operations, manage trade lifecycle processes, ensure accurate reporting, and improve workflows through collaboration and automation.

As a Junior Data Engineer, you will build data processing pipelines, support decision-making, visualize finance indicators, and monitor improvements.

This role involves designing, building, and operating AI-ready cloud platforms, focusing on public cloud infrastructure and AI service delivery in a regulated environment.

The AI Adoption SME will facilitate the adoption of AI tools within teams, conduct training, create best practices, prototype workflows, and monitor adoption metrics for effective AI integration.

The role focuses on building product reports for the Connected Store, managing ETL processes, utilizing BI tools, monitoring KPIs, and collaborating with teams.

Design, build and maintain infrastructure tooling for deployment, observability, orchestration, disaster recovery and CI/CD to support scalable, highly available production systems and customer integrations.

Run and maintain production infrastructure for Thought Machine's cloud-native core banking and payments SaaS. Automate fleet management, disaster recovery, backups and capacity planning; participate in design reviews, on-call rotations, and reliability-focused feature design. Mentor team members and maintain operational documentation and runbooks.

Build and maintain production-ready infrastructure tooling and automation for deployment, observability, orchestration, backup/disaster recovery, and CI/CD integrations to support scalable, highly available services.

Design, implement and maintain scalable, performant microservices; write automated unit and integration tests; manage deployments from testing to production; collaborate with engineering teams; translate customer requirements into deliverables and tickets.

Lead resolution of high-priority cloud incidents across hosted and self-managed Vault deployments. Mentor junior engineers, build tooling and automation, perform root cause analysis, improve observability and support processes, and act as the technical owner for enterprise relationships to enhance platform stability and client outcomes.

Build end-to-end features across frontend and backend, design scalable secure services, write automated tests, debug to production, translate customer requirements, and collaborate across cross-functional teams.

Lead and manage a team of engineers to deliver the product roadmap; collaborate with Product and Client Services; participate in design reviews; measure team impact; contribute to product strategy and engineering initiatives; perform hands-on coding, code reviews, and support career development and recruitment.

The role requires leading the AI & Services engineering team, focusing on technical direction, team growth, and product delivery, with an emphasis on engineering excellence.