Top Python Jobs in London

Leads UK-hosted cloud infrastructure design and deployment across cloud, on-premise, air-gapped, and secure environments. Builds infrastructure as code, manages Kubernetes and CI/CD systems, hosts approved AI models, improves developer tooling, supports Hardware in the Loop integration, and troubleshoots distributed systems. Partners with product managers, customers, and global infrastructure teams to deliver secure technical solutions for defense and national security programs.

Build and own end-to-end trading products, client portals, internal applications, backend services, APIs, data models, and frontend experiences. Design scalable, high-performance systems using modern frontend and cloud technologies, collaborate with product, marketing, trading, and engineering teams, and contribute to platform architecture and corporate website development. The role requires secure full-stack development, real-time data integration, cloud infrastructure knowledge, and database expertise.

Build and own frontend-focused, full-stack web applications for B2B retail customers. Responsibilities include creating responsive real-time interfaces, simplifying complex AI capabilities, contributing to APIs and system design, and managing testing, observability, deployment, and post-release investigation. The role requires strong TypeScript and React expertise, real-time communication experience, cloud deployment skills, product judgment, rapid delivery, and experience using AI coding tools.

Build and maintain machine learning pipelines for market pricing, productionize Python models and data science workflows, and improve testing, release, monitoring, versioning, and governance. Investigate data, model, and pipeline issues; automate manual processes; and ensure workflows are traceable, auditable, documented, and reliable. Collaborate with pricing, data science, data engineering, ML engineering, governance, and business stakeholders in a regulated environment.

Build and maintain machine learning pipelines for market pricing, productionise Python models and data science workflows, and improve testing, deployment, monitoring, versioning, documentation, and governance. Investigate data, model, and pipeline issues; automate manual processes; and collaborate with Pricing, Data Science, Data Engineering, ML Engineering, and governance teams in a regulated environment.

Leads and develops high-performing engineering teams responsible for learner growth or monetization products. Sets technical and product strategy, drives execution, coaches engineers, guides architecture and technical trade-offs, and promotes engineering best practices, reliability, quality, and continuous improvement. Partners with Product, Data, and Design to prioritize high-impact initiatives and deliver measurable customer and business outcomes.

Principal Solution Engineer responsible for helping UK customers evaluate and adopt Snowflake. Partners with sales teams, channel partners, and customers to present solutions, conduct demos and proofs of concept, design architectures, develop technical champions, and secure technical wins. Requires strong modern data, cloud, SQL, presentation, and customer-facing skills. The role also involves competitive positioning, partner collaboration, account planning, and representing Snowflake at industry events.

Investigate and resolve complex escalated issues for cloud video security products by reproducing problems in lab, analyzing logs and network traces, collaborating with R&D/test/support/sales, testing fixes and workarounds, writing technical documentation, and occasionally visiting customer sites.

Lead high‑impact AI and decisioning projects from discovery through production. Define technical roadmaps, design and validate models (including causal/experimentation), partner with engineering to productionise services with monitoring and governance, mentor data scientists, and promote responsible AI practices and platform adoption.

Build, deploy, and maintain production ML and AI systems: model packaging, lifecycle automation, monitoring, batch and real-time workloads, and platform improvements while collaborating with data scientists, engineers, and product teams.

Lead design and deployment of ML models and pipelines for the AI platform. Translate business problems into measurable ML solutions, design experiments and A/B tests, and own model performance, monitoring, degradation detection and retraining. Champion responsible, explainable AI in a regulated financial context, choose between classical ML, LLMs and agentic approaches, collaborate with ML engineering, product and commercial teams, and mentor junior data scientists.

Lead design and ownership of an end-to-end AI platform for large-scale telecommunications. Define architecture, integration patterns, and standards; guide engineering, ML, and operations teams; ensure scalability, observability, security, and cost efficiency; support vendor evaluations, M&A technical due diligence, and stakeholder communication to deliver measurable business outcomes across multiple European markets.

Provide day-to-day actuarial pricing support to underwriting teams, maintain and validate rating tools, rebuild models in hx Renew using Python, produce portfolio and regulatory reporting (PMDR, Actuarial Function Report), and support a multi-year pricing transformation while progressing toward actuarial qualifications.

Develop and deliver end-to-end Kotlin/JVM services and features for greenfield and brownfield projects. Collaborate on design, code reviews, testing, deployment, monitoring, and integration with internal/external APIs and cross-functional teams to meet product goals.

The Graduate Machine Learning Researcher will design, test, and implement machine learning models to improve predictive accuracy in sports betting analytics. In a collaborative environment, they will interface with experienced professionals and be involved in R&D from design to implementation, utilizing their mathematical insights.

Provides advanced technical support to enterprise customers, troubleshooting cloud infrastructure, networking, Linux systems, containers, and security issues. Performs root cause analysis, supports deployments, maintains SLAs, documents solutions, and collaborates with engineering, product, and sales teams. The role also mentors junior staff, contributes to training resources, and helps optimize infrastructure as code, observability, identity management, databases, and customer environments.

Build, maintain, and troubleshoot scalable AWS data pipelines using Python, PySpark, Spark, and Airflow. Perform root-cause analysis of pipeline and data-quality issues, apply dimensional modeling and slowly changing dimensions, and deliver governed data assets. Provision infrastructure with Terraform, containerize solutions with Docker, and manage GitLab CI/CD deployments. Work with AWS security, encryption, IAM, monitoring, and analytics services in a regulated government environment.

Migrate SQL Server data products and analytical workloads to a modern cloud platform. Redesign legacy SQL, ETL processes, and business logic; build scalable pipelines and analytical models; validate data quality; collaborate with stakeholders; and improve platform reliability, performance, cost efficiency, and AI-assisted data engineering automation.

Build and extend the platform layer: design shared backend services and APIs, improve reliability and correctness, collaborate with product teams to remove platform bottlenecks, mentor engineers, shape architecture and migrations, and write high-quality fullstack code with a backend focus.

Design and evaluate memory architectures for foundation models across modalities. Build production-ready, scalable learning models and algorithms, define memory evaluation metrics, collaborate with researchers and engineers, and guide roadmap decisions for long-horizon model behavior and efficient memory storage/retrieval.

Build and maintain backend services, APIs, and data pipelines for Modo's energy market platform. Own AWS infrastructure with Terraform, implement monitoring, and contribute to LLM-powered features. Collaborate with analysts and data scientists and split time between new features and platform health.

Lead data strategy and engineering for AD/ADAS: collect, sample, label, and curate large-scale vehicle and simulator data; build evaluation frameworks and scalable pipelines; analyze data to improve perception and planning models; collaborate across teams and mentor colleagues to deploy production-ready ML solutions.

Lead and manage competition economics projects, conduct antitrust analyses, produce clear written reports, manage client relationships, coach team members, and support business development and resource allocation.

Manage securities and financial litigation projects using econometric and statistical techniques. Lead quantitative analyses of market manipulation, deliver reports and presentations, manage client engagements, mentor team members, and support business development.

Lead FIX client onboarding and integrations across FX, equities, and digital assets. Manage projects from requirements through certification and production go-live; configure, test and validate FIX sessions; troubleshoot connectivity and production issues; provide frontline EMEA technical support; document procedures and collaborate with engineering, product, and account teams while using AI/automation to streamline processes.