Top Python Jobs in London

Lead design and delivery of enterprise-scale data ingestion, orchestration, and provisioning solutions. Build trusted, governed data products and event-driven integration capabilities (APIs, Kafka), ensure data quality, observability, CI/CD, and operational resilience, and provide technical leadership across platform, application, and business teams to support analytics, regulatory reporting, ML/AI, and operational systems.

Lead design and delivery of scalable GCP-based data pipelines and models for real-time AI/ML and batch workloads. Own architecture, automation, IaC, security, monitoring, cost optimisation, incident resolution, and mentor engineers while translating business needs into reliable data solutions.

Build and maintain scalable GCP data pipelines and databases to support real-time AI/ML and analytics. Design data models, automate workflows with orchestration tools, ensure data security and governance, provide second-line support for incidents, optimise cost and performance, and collaborate with cross-functional teams to deliver reliable data solutions.

Provide technical pricing support for a Marine insurance portfolio: develop, validate and deploy pricing models, support case pricing and renewals, monitor portfolio performance, deliver pricing insights and liaise with underwriting and other actuarial teams.

Provide responsive customer support for IDBS life-sciences software via email, web and community channels; perform initial troubleshooting, escalate complex cases, document solutions in the knowledge base, collaborate with cross-functional teams, learn ITIL-based processes, work rotating shifts (8:00–21:00 GMT) from the Woking office, and drive continuous improvement.

Design, build, and operate production AI systems and agents for private equity workflows. Own agent harness, tool integrations, retrieval/search, evals, and document ingestion pipelines. Ship and iterate features end-to-end to meet professional reliability and citation standards, working across backend and ML infrastructure with product and engineering teams.

Design, build, and operate backend systems for an AI platform: agentic workflows, document ingestion and search at scale, streaming execution, APIs and data models. Own features end-to-end from ideation to production, measure impact, and maintain services in production.

Build and operate end-to-end product features across the full stack, from design and architecture to production. Ship high-impact software, maintain code quality, work with LLMs/agents and search/OCR pipelines, and collaborate in a fast-paced, startup engineering team.

Build and lead energy-systems modelling workstreams informing decarbonisation pathways (power, hydrogen, storage, industry). Design and deliver modelling tools, collaborate with platforms and partners, and apply advanced analytics to drive system-level sustainability impact.

Design, build and deploy enterprise-scale ML and AI solutions (including LLMs and RAG) to improve operational efficiency, service resilience and customer outcomes. Perform statistical modelling, feature engineering, experimentation, and large-scale data analysis. Move models from prototype to production, support monitoring/governance, and partner with engineering, SRE, product and business stakeholders to define metrics and deliver measurable business value.

Design, build, and own the AWS foundation and Terraform IaC; develop self-service developer-platform tooling; manage CI/CD and deployment fabric; embed security and networking into platform defaults; implement observability and cost controls; and support research teams to scale while enabling self-service workflows.

Maintain CRM/marketing data hygiene, build and test audiences in Braze, manage Segment↔Braze data flows (ETL/reverse-ETL), troubleshoot syncs, document mappings, and ensure GDPR-compliant handling while liaising with marketing stakeholders and reporting to the Data Director.

Develop, test and maintain embedded firmware for Brompton Electric bikes across the full product lifecycle. Collaborate with cross-functional teams to design and ship features, debug issues, write scalable C++ code, participate in code reviews, and support manufacturing and production releases.

Configure synthetic populations and onboard customer datasets, validate synthetic methodologies, lead technical client engagements, train and scale product adoption, translate insights for executives, and feed customer feedback into product priorities.

Design, build, and operate production-grade generative AI applications (copilots, RAG pipelines, agents). Partner with business teams from discovery through rollout, implement eval-driven testing, observability, cost controls, security/privacy/compliance, and codify reusable patterns and runbooks. Own integration with enterprise systems and apply responsible-AI governance.

Work with Risk Management to gather requirements and develop/enhance risk systems. Build data analysis processes, valuations, and custom measures; create dashboards and reports; integrate systems with trading and middle-office; manage reference data; document processes, implement source control and deployment best practices, and evaluate new technologies.

Design, build, and deploy intelligent AI agents for e-commerce and logistics. Develop agent architectures using ML, NLP, reinforcement learning, and multi-agent techniques; integrate with JD systems; run experiments, monitor performance, and collaborate with cross-functional teams to deliver scalable, production-ready solutions.

Lead and define strategy, architecture, development and rollout of MUFG's international Credit Risk analytics platform. Manage a distributed team to deliver PFE and other credit risk measures, ensure regulatory compliance, guide technical design as credit risk SME, oversee vendor/stakeholder interactions, and drive continuous improvement, security, and audit readiness across the risk IT estate.

Build and maintain pricing, risk, portfolio construction and analytic tools for derivatives and derivative strategies. Model risks across fixed income and other assets, support portfolio managers with analysis, participate in IT and process projects, and ensure instruments are priced and reported in line with market conventions.

Develop, implement and monitor statistical and machine learning models for commercial lending. Optimize and experiment with model frameworks, source alternative data, present insights to stakeholders, mitigate risks, and apply AI/advanced prompting to automate workflows and drive value.

Lead design, build, and commission in-house test rigs and fixtures for humanoid robot subsystems and full robots. Define validation scope with system owners, specify and source test equipment, manage vendors and budgets, implement mechanical and electrical designs, and support long-term reliability, certification, and data acquisition for validation programs.

Build and evolve a cloud-based data and ML platform: implement IaC and CI/CD, develop Python/Spark data components, support ML/AgentOps lifecycle, enforce security and observability, and collaborate with data and ML teams to enable platform adoption and governance.

Build and own backend-focused full‑stack product features using Python and React; design data schemas and architecture; write well‑tested code; review peers; monitor production systems; collaborate with cross‑functional teams and integrate third‑party APIs.

Lead and grow an SDET team building reliable, scalable cloud storage solutions. Provide technical leadership, design and review architectures, plan sprints, implement deterministic functional and non-functional test suites in CI/CD/CT pipelines, collaborate on product specs, hire and mentor engineers, and continuously improve processes and systems.

Support Marketplace (POP) growth by analyzing business performance, building dashboards and forecasts, monitoring KPIs (GMV, orders, revenue, conversion, fulfillment), identifying opportunities, supporting cross-functional strategic initiatives, automating reporting, and presenting insights to senior management.