Top Python Jobs in London

Lead DevOps pipeline design and implementation, advise clients on DevOps best practices, establish DevOps functions, and engage stakeholders to ensure seamless delivery across projects.

Design, build, and maintain scalable Azure cloud infrastructure and data platforms using Terraform. Build CI/CD pipelines, deploy and support Databricks, Event Hubs, and ADLS Gen2, automate operations with Python/Bash, administer Linux environments, optimize SQL systems, ensure security and governance, monitor performance and costs, and support real-time streaming data pipelines.

The Forward Deployed Engineer leads customer-facing deployments of AI models, building full-stack systems, scoping work, and delivering value under ambiguity. They ensure quality delivery and share feedback to influence product improvements.

Lead and implement end-to-end ML solutions: translate vague requirements into models, run ML experiments, apply GenAI, design ML architectures on Google Cloud, build production-grade code, handle MLOps, data engineering, optimization, deployment, and client-facing project leadership.

Join the Data Science team to innovate solutions for data problems, develop forecasting models, and enhance quant strategies using machine learning.

The Pricing Actuary will handle actuarial pricing for Political portfolios, support broker negotiations, and develop pricing capabilities. They will collaborate with the Actuarial team and monitor portfolio performance, leveraging strong IT and technical pricing skills.

This role involves conducting risk and capital analysis for Lloyd's syndicates, focusing on regulatory and economic capital requirements, model development, and stakeholder communication.

Build and maintain backend services for Depop's shipping journey. Design scalable systems, own features end-to-end, handle production incidents, contribute to architecture, collaborate cross-functionally, mentor teammates, and support CI/CD and testing practices.

Lead design, implementation, and operation of enterprise-scale international data platforms. Build and mentor global data engineering teams, define architecture and governance, ensure scalability, reliability, security, and cost optimization, and partner with analytics and business stakeholders to deliver data solutions and demonstrate ROI.

The Staff Backend Engineer will lead the technical vision for Depop's data platform, focusing on data ingestion, scalability, observability, and architecting data solutions while mentoring team members.

As a Senior Machine Learning Scientist at Depop, you'll design and deliver ML solutions for search and ranking, conduct experiments, and collaborate with product and engineering teams.

Build predictive models and statistical analyses using alternative and traditional market data, produce reproducible Python/SQL workflows, conduct research, collaborate with investment teams to generate actionable insights, communicate findings to non-technical stakeholders, and support data engineering and best-practice development.

Lead design, operation, and automation of Fastly's global edge network. Respond to and lead network incident resolution (BGP/anycast), build automation and monitoring, analyze traffic and performance, mentor teammates, and partner with engineering to improve network reliability and tooling.

Lead and shape the Adversary Emulation (internal Red Team) programme: plan and run complex offensive security operations, provide technical leadership and stakeholder reporting, develop tooling and team capabilities, and coach team members to improve organisational security outcomes.

Design, build, and operate a hybrid on‑prem/cloud compute platform for interactive and large-scale batch computing. Develop CI/CD-driven containerized environments, optimize application performance at scale, consult scientists on scalability, ensure observability, testing, documentation, and mentor team members to drive platform adoption and reliability.

Designs, builds, and operates hybrid on-prem/cloud compute platforms, toolchains, CI/CD, and workflows for interactive and large-scale batch scientific computing. Consults scientists on scalability and performance, produces well-engineered software with tests and docs, ensures logging/lineage and platform consistency, and supports transition of HPC users to the platform.

Develop and evaluate machine learning models linking DNA sequence and genetic variation to molecular phenotypes and disease. Build sequence-to-function models (variant effect and regulatory activity prediction), integrate sequence representations with transcriptomic and epigenomic data, collaborate with experimental teams to validate hypotheses, communicate results, and contribute to publications and documentation.

The Senior Pricing Analyst at Zego will guide the pricing strategy for motor products, lead pricing models development, work cross-functionally, and mentor junior team members.

The Quant Analyst will develop pricing tools for swaps, work on data analytics, validate models, and participate in market research.

The High-Touch Execution Strategist will manage execution processes, analyze market microstructures, and collaborate with traders to enhance trading practices.

Four-month, full-time research fellowship focused on ML systems and performance. Fellows build and evaluate infrastructure-heavy projects (e.g., CPU simulators, accelerator backends, large-scale distributed training), use external models/APIs, receive mentorship, funding for compute, and aim to produce public research outputs.

Four-month full-time research fellowship mentoring fellows to run empirical RL and LLM projects using external infrastructure. Fellows receive compute funding and a weekly stipend, produce public outputs (e.g., papers), and work on RL environments, algorithms, model fine-tuning, and training/evaluation of large models with mentor support.

4-month full-time funded research fellowship using external models/APIs to produce public outputs (papers). Fellows receive mentorship, workspace access (Berkeley or London) or remote options within US/UK/Canada, weekly stipend, compute funding, and are expected to implement experiments, collaborate with mentors, and communicate results. Applicants must be fluent in Python and authorized to work in the US, UK, or Canada.

Four-month full-time research fellowship supporting empirical AI safety projects using external models and APIs. Fellows receive mentorship, compute funding, and workspace access to produce public outputs (e.g., papers) across safety, robustness, interpretability, RL, and societal-impact topics.

Partner with stakeholders to discover AI use cases, configure enterprise GenAI tools, build and maintain high-quality prompts, contexts, and RAG/document-intelligence pipelines, evaluate and improve AI outputs, create reusable playbooks/templates, and enable teams on governed, production-ready AI workflows.