Top Python Jobs in London

Own end-to-end quality validation for new features and releases on a genomics platform. Design, build, and maintain scalable automated regression suites (Playwright/Cypress/Selenium), run API/integration tests (Postman/Swagger), integrate tests into CI/CD, lead exploratory testing and release readiness, track defects to resolution, improve QA processes, and mentor junior QA engineers while communicating quality risks across teams.

As a Technical Lead, you will guide software engineering teams, translate client requirements into applications, ensure best practices, and shape technical direction while mentoring team members.

As a Senior Data Engineer, you will design and develop large-scale data processing software, manage technical components, and mentor team members, while ensuring code quality and operational readiness.

As Deployment Strategist Lead, you will open a new market, build a team, engage with strategic customers, and ensure effective implementation of AI voice technology, while collaborating with the company's product and research teams.

The Site Reliability Technical Lead will oversee system design, enhance platform reliability, manage incidents, drive automation, and mentor engineers to ensure scalable and secure solutions.

As a Data Scientist, you will design and deploy data-driven fraud prevention solutions, working directly with clients to tackle unique challenges. You'll build machine learning models and collaborate with engineering to enhance backend systems.

As a Machine Learning Engineer, you will develop production-ready ML solutions, collaborate with multidisciplinary teams, and contribute to Defence and National Security challenges.

As a Machine Learning Engineer, you will deploy AI/ML systems, translate client needs into solutions, and engage with users to provide support and improvements.

The role requires deploying AI solutions and automations for clients, building prototypes, integrating systems, and collaborating with various teams while ensuring effective client interaction.

The QA Engineer will enhance test automation frameworks, perform cross-functional testing, and ensure the quality of ClickHouse's cloud and open-source offerings.

Create high-quality data science tutorials and articles, conduct research on trends, suggest topics, and use AI tools for content enhancement.

Build fault-tolerant, reliable cloud backend services for a hyperscaling AI platform, including compute, storage, networking, managed Kubernetes, databases, billing, monitoring and ML services.

Build and own end-to-end backend systems for forecasting and agentic LLM research: design, deploy, monitor, debug, and harden features and pipelines (benchmarks, agents, production services). Prototype quickly, work with LLM APIs and coding agents, and collaborate with researchers to improve evaluation and forecasting tools.

Lead analytics strategy and partner with Finance, Sales, Marketing, and Product to design, automate, and maintain metrics, dashboards, and analyses. Ensure data quality (dbt), build scalable analytics solutions, embed AI-driven and agentic workflows, and translate insights into actionable business outcomes to improve acquisition, retention, and growth.

Deliver technical implementations of the Watershed platform: build integrations and data pipelines, perform analysis and reporting, consult on best practices, provide client-facing technical support and training, automate deployments with CI/CD, and occasionally contribute to core product updates.

Build and scale backend systems for a large social game. Design microservices and distributed systems, implement backend best practices, ensure reliability, security, and performance, collaborate cross-functionally, drive DevOps and testing, and continuously improve processes.

Monitor and analyze product and advertising KPIs, integrate data from multiple sources, build and optimize weekly/monthly marketing reports, run A/B test analyses, create campaign summary reports, and provide actionable recommendations to improve campaign performance.

As a Senior Platform Engineer at Kainos, you'll design and support components of a digital service platform using modern automation and cloud technologies, collaborating with teams to ensure high-quality delivery and continuous improvement of services.

Lead a small squad to design, build, and ship new origination product categories and deep integrations. Translate ambiguous commercial goals into deliverable technical plans, mentor engineers, make risk judgments for deal-gating tooling, and represent technical direction to commercial and international stakeholders. Stay hands-on on the hardest technical work and ensure new products drive origination pipeline outcomes.

Lead deployment, configuration, and optimisation of enterprise software for customers. Design scalable Azure infrastructure using Terraform, deploy containerized apps on Kubernetes/Docker, manage SQL Server/PostgreSQL, automate tasks with PowerShell/Bash/Python, implement monitoring/observability, run workshops, and provide post-go-live support and documentation.

Build and maintain tools for merchandisers to manage product discovery. Deliver features for the Searchandizing dashboard, improve usability, own full stack projects from idea to production, work with PMs/Designers/EMs, and handle testing, CI/CD, deployment, and production ownership.

The Technical Recruiter will manage end-to-end hiring processes for engineering roles, build talent pipelines, and partner closely with hiring managers to identify hiring needs while ensuring a positive candidate experience.

Design and build end-to-end ML systems for fraud detection: develop and deploy models, create production-ready features and real-time data pipelines, integrate with backend services, and ensure monitoring, security, and observability.

Lead the development and optimization of machine learning algorithms, owning the end-to-end model development and collaborating with Data Engineers for integration into live systems.

Design, build and optimise Python-based AI applications and data storage solutions. Collaborate with clients and teams, enforce code quality, CI/CD, testing practices, and deliver scalable production systems across cloud environments while travelling to client sites.