Top Python Jobs in London

Validate and benchmark ML models and stacks on Graphcore hardware. Build automated benchmarking pipelines, run open-source models, create targeted tests for numerical precision, quantisation, distributed execution and subgraphs, and debug performance and correctness across frameworks and execution environments.

Validate and benchmark ML models on Graphcore's software/hardware stack. Create automated benchmarking pipelines, run open-source models, design targeted tests for numerical precision, quantisation, attention, distributed execution, and debug performance and correctness issues across frameworks and environments.

Design and build test infrastructure, automation, and tooling to validate ML software stacks and hardware; shape test architecture across CI pipelines, frameworks, simulators, emulators, and large ML workloads; mentor engineers and own complex validation projects.

The Platform Engineer will design and maintain AWS infrastructure, implement CI/CD pipelines, and enhance platform reliability through Kubernetes management and observability practices.

The Senior GenAI Software Engineer will architect AI systems for ad creatives, prototype solutions, and mentor teams while driving innovation in generative AI applications.

Lead design and implementation of scalable backend and frontend systems, own domains end-to-end, set technical strategy and architecture, mentor engineers, drive cross-team initiatives, and improve reliability, performance, testing, monitoring, and CI/CD for customer-facing microservices.

Lead analytics for customer operations: build capacity planning and forecasting models, own data pipelines, develop predictive and causal inference analyses, track KPIs, standardise processes, and partner with operations, WFM, quality, and training to drive data-driven improvements.

Partner with financial crime product teams to drive analytics for screening controls. Build and maintain data pipelines, create reports and visualisations, define and track key metrics, run discovery analyses to improve controls and customer experience, and collaborate with stakeholders to translate insights into product changes.

Senior Data Scientist embedded in international teams to ingest, validate, and transform partner oncology data into research-grade datasets. Build and automate scalable pipelines, apply ML/LLM techniques to unstructured EHR data, and collaborate with cross-functional stakeholders to develop and deploy real-world data products.

Develop and maintain internal build, test, and integration tooling for the ML software stack. Build release processes, assist dependency management, guide developers on build best practices, collaborate with QA and engineers to resolve integration issues, and contribute fixes to the ML software stack.

Design, deploy, and maintain tools and services for build, CI/CD, packaging, and releases. Manage cloud and Kubernetes infrastructure, use IaC, reduce toil, and support junior engineers for reliable ML software delivery.

Partner with trading, risk, operations, data and technology stakeholders to elicit and document requirements, define current and future-state operating models, produce user stories and functional specs, support Agile delivery (Azure DevOps), ensure traceability, and support testing, UAT and implementation for energy trading transformation programmes.

Build, operate, and maintain infrastructure and tools for ML teams: deploy services with Kubernetes/Docker, manage cloud infrastructure (Terraform), support CI/CD and ML workflows, and integrate observability and accelerator tooling.

Early-career role supporting 4G/5G RAN test activities: learn tools and processes, run and document test cases, collect logs/KPIs, use automation frameworks, assist environment setup, and collaborate with integration and network engineers while improving test scripts and reporting defects.

Early-career role supporting 4G/5G RAN testing: learn and shadow, prepare and run test cases, collect logs and KPIs, use automation frameworks and Linux tools, record results in Azure DevOps/Jira, assist environment tasks, and contribute small automation improvements.

Act as a subject matter expert in currency hedging for product launches, manage operational oversight of currency hedged ETFs, and drive process improvements.

Lead strategy, architecture and implementation of test automation frameworks for web and mobile. Design and maintain UI, API and service tests, integrate tools into CI/CD, manage cloud testing, run performance and accessibility testing, and mentor engineers to drive quality engineering across projects.

SREs at Citadel focus on optimizing and maintaining system reliability, performance, and automation for investment applications, collaborating closely with teams.

As a Quantitative Researcher intern at Citadel, you'll develop models, implement trading strategies, and conduct statistical research in finance.

Lead process assessments and identify automation opportunities, document current and future state processes, collaborate with clients and developers, and troubleshoot automation issues.

The Senior Data Scientist will lead the delivery of data science solutions, mentor teams, and develop ML models to address business challenges.

The Principal Forward Deployed Architect leads enterprise transformations using the Atlassian platform, designing scalable systems across business functions, guiding AI adoption, and mentoring teams to ensure successful implementation and architecture delivery.

You'll partner with senior leaders to define and improve reliability metrics, influencing decisions based on data insights and system performance.

As a Senior Software Engineer, you'll innovate and maintain scalable systems in a multi-disciplinary Agile team, focusing on sports betting products.

Join a multidisciplinary Agile team to design, build and maintain highly distributed, real-time, cloud-native sportsbook and risk-management systems. Contribute across the stack (front-end, back-end, infrastructure), apply good software design, TDD, CI/CD and scalable microservice patterns, and collaborate with DevOps, Data Science and QA to deliver high-quality, observable products.