Top Python Jobs in London

Embed with enterprise customers to discover use cases and build production multimodal agent systems (voice, video, text). Architect RAG and MLOps pipelines, deploy and optimize LLM-powered agents, implement observability and evaluation, and integrate agents into customer systems while advising stakeholders and delivering fast POCs.

Partner with sales and ML teams to lead technical strategy for complex enterprise deals. Run deep discovery, design integrations, build customized demos and end-to-end POCs, write production-quality Python scripts for data pipelines and API integrations, and advise on security, architecture, and multimodal/robotics data workflows while relaying customer feedback to Product and Engineering.

Own end-to-end publisher integrations (SDK, oRTB, VAST, web tags), provide technical account support, troubleshoot integrations, use SQL to surface insights, and coordinate with Product, Supply, and Data Science to improve tooling and processes.

Lead and own LoopMe's AI throttling system and related AI products end-to-end. Manage a team of four data scientists/ML engineers, define roadmap, partner with commercial and operations teams, deploy and monitor production models, measure causal business impact, and maintain technical quality across modelling and systems.

Design, develop, and maintain scalable automation frameworks and programmatic IaC (Python, Jinja2, Terraform). Build Puppet and PowerShell automation for mixed Linux/Windows environments, integrate automation with CI/CD, implement testing strategies, and partner with cloud/platform teams to standardize and operationalize infrastructure at scale.

Lead backend architecture and delivery for large-scale multiplayer game services. Architect distributed systems, write code, deploy infrastructure, mentor engineers, liaise with clients, design cost estimates, enforce best practices, and drive CI/CD, security, and production readiness.

Full-stack AI/ML Software Engineer to build HealthTech SaaS microservices, implement and integrate ML solutions, write high-quality code, author documentation, perform code reviews, and act as an SME on services and systems.

Design, build, deploy and maintain backend services for large-scale multiplayer games. Collaborate with peers and stakeholders on estimates, implement features, ensure CI/CD, docs, security, and support team members while operating autonomously in a remote environment.

Develop and optimize performance-critical components of a low-latency trading platform (pricing engines, gateways, market-data, messaging). Own design, deployment, production support, observability, and architectural decisions. Mentor engineers, conduct reviews, and ensure reliability in cloud-native AWS and colocated environments.

Build and maintain low-latency trading infrastructure on Linux using modern C++ and Go. Work on pricing engines, connectivity, market-data pipelines, FIX integrations, messaging, observability, and production support. Own design, deployment, incident response, and continuous performance optimization.

The Senior Data Engineer will enhance backend systems for a social media app by managing databases, optimizing recommendation algorithms, and ensuring accurate recommendations.

The AI Engineer designs, develops, and deploys AI-driven applications for non-data scientists, enhancing decision-making and model accessibility for organizations.

The Site Reliability Engineer will design, build, and maintain AWS cloud infrastructure, ensure performance and reliability, automate tasks, and participate in incident management.

The Data Scientist supports customer use of the Epistemix platform through data integration, modeling, and visualization, improving decision-making and customer satisfaction.

The Senior Back-End Software Engineer designs, develops, and maintains scalable backend systems while taking ownership of the software development lifecycle.

Join a small engineering team to build innovative healthcare products using a modern tech stack. Drive product development focused on lab testing and patient experience. This role requires 3+ years of backend experience, preferably in Python, and a passion for technology's role in healthcare.

Lead and execute statistical programming activities including migration to SAS Viya, development of tables/listings/figures and derived datasets, CDISC compliance (SDTM/ADaM/DEFINE.XML), process improvement, mentoring, quality control, regulatory submission readiness, client interfacing, and contributing to SOPs and business development. Ensures documentation, inspection readiness, and adherence to industry standards.

The Senior AI Compute Infrastructure Engineer will manage and optimize GPU and accelerator clusters for AI workloads, collaborate with teams, and ensure reliable performance and cost efficiency.

As a Software Engineer at Canonical, you will design, build, and ship software, improve packaging and distribution processes, and mentor colleagues while contributing to open source projects.

The Junior Ubuntu Software Engineer will design, build, and ship software, focusing on quality and resilience, while engaging with the open source community.

The Ubuntu Engineering Lead will oversee and mentor teams, drive the development and delivery of high-quality software, and contribute to community engagement while managing technical roadmaps and cultivating engineering talent.

Design, implement, and maintain integration- and API-level automated tests for a distributed, cloud-native SaaS platform. Validate asynchronous/event-driven workflows and failure modes, build performance and scalability tests and data, integrate tests into CI/CD, analyse test results and telemetry, and collaborate with product and engineering teams to improve reliability, observability, and release readiness.

Design, implement, and maintain integration- and API-level automated tests for a distributed, cloud-native SaaS platform. Validate asynchronous/event-driven workflows, build performance and scalability tests, integrate tests into CI/CD pipelines, analyze failures with logs/telemetry, and collaborate with product and engineering teams to improve reliability, observability, and release readiness.

Develop, validate, and deploy machine learning and statistical models for soccer betting products. Create soccer-specific features, run offline and online experiments, collaborate with data engineering and product teams, follow software engineering best practices, document work, and present findings to technical and non-technical stakeholders.

Design, train, evaluate, and deploy NLP and LLM-based models for document processing, parsing, classification, search, and matching. Own end-to-end ML architecture, run experiments, apply robust development/testing practices, and improve AI tooling and standards.