Top Python Jobs in London

Lead architecture and engineering for B2B agentic commerce and machine-learning systems in global payments. Define multi-agent architectures, authorization, information barriers, MLOps pipelines, evaluation frameworks, safety guardrails, and model-risk evidence. Develop and review secure production code, establish AI-assisted engineering standards, integrate external agents, improve operational resilience, and guide technical teams and vendors. The role requires advanced Python, production LLM agent experience, secure distributed-systems expertise, and financial-services technology knowledge.

Leads the design, productionization, and operation of LLM-powered agentic commerce applications. Builds retrieval systems, agent memory, organizational context, multi-agent workflows, evaluation frameworks, guardrails, and ML pipelines. Deploys resilient, observable solutions on AWS or Azure using MLOps practices, while partnering with product, business, data science, and engineering stakeholders to deliver secure, auditable production agents.

Designs, automates, operates, and hardens enterprise-scale Hyper-V and VMware VCF virtualization platforms across global data centers. Responsibilities include cluster architecture, provisioning, patching, performance analysis, full-stack troubleshooting, capacity planning, vulnerability remediation, production change management, CI/CD automation, documentation, and mentoring. The role also promotes validated, auditable AI-assisted infrastructure engineering practices.

Leads commercial analytics and insights for pharmaceutical brands across the UK and Ireland. Responsibilities include market, customer, competitive, and performance analysis; forecasting market, patient, and revenue outcomes; designing market research projects; supporting dashboards and data platforms; and advising senior commercial leaders. The role also drives customer segmentation, campaign optimization, next-best-action initiatives, analytics innovation, and coaching of junior colleagues.

Analyze market, customer, brand, and competitor data to generate commercial insights, track KPIs, support forecasting and market research, maintain dashboards, and inform strategy. Partner with commercial and DD&T stakeholders on segmentation, targeting, campaign optimization, and data-driven decision-making while contributing to cross-functional projects.

Owns the technical systems, data infrastructure, automation, and reusable assets that improve global Solutions Consulting operations. Builds tools using scripting, APIs, AI development platforms, and business intelligence systems; converts field feedback into prioritized initiatives and measurable outcomes; produces leadership insights; drives adoption; and partners across architecture, POC delivery, security, privacy, partnerships, and RFP teams.

Build and maintain full-stack SaaS features across backend and frontend: develop scalable Python and .NET services, create React/TypeScript UIs, design and integrate REST/gRPC APIs, support cloud-native deployments, production monitoring, incident resolution, and apply security, CI/CD, and testing best practices while collaborating with product and business stakeholders.

Build and own evaluation infrastructure for AI agents, including CI/CD pipelines, scorers, datasets, annotation workflows, observability tools, and diagnostic systems. Run experiments across prompts, models, and agent harnesses to improve quality, latency, and cost. Lead the AI Quality engineering team while remaining hands-on, partnering closely with AI Core engineering to validate production improvements.

Build and operate scalable ML platform infrastructure supporting batch and real-time model workloads. Responsibilities include model deployment, serving, lifecycle automation, monitoring, observability, incident response, documentation, and collaboration with data scientists and engineering teams. The role also contributes to platform architecture, data products, reliability, technical standards, and data warehouse initiatives.

Design and maintain scalable data platform infrastructure, ingestion pipelines, ETL/ELT workflows, data models, governance, reliability, and observability. Collaborate with analytics and engineering teams, support data warehouse architecture, participate in on-call incident response, document operational processes, and establish strong engineering practices for analytics and future AI capabilities.

Develop and deploy machine learning and generative AI solutions for payments and banking operations. Build LLM-powered workflows, evaluation frameworks, ML services, and production deployment pipelines. Apply MLOps practices including monitoring, testing, versioning, governance, and rollback. Collaborate with product, risk, operations, and technology teams while documenting models, communicating results, and ensuring secure, reliable, and compliant production systems.

Build and scale full-stack services supporting international SMS expansion and RCS capabilities. Design new services, work across monolithic and microservices architectures, optimize databases and application performance, develop CI/CD pipelines, debug production issues, and collaborate across teams. The role involves Python, Django, Go, React, AWS, distributed systems, and modern DevOps tooling, with a focus on reliable mobile messaging products for global customers.

Lead data science for Wise’s AML Risk team by developing machine-learning and GenAI detection systems, optimizing precision-recall tradeoffs, building coverage frameworks, and deploying production Python services. Hire and mentor specialists, collaborate with product, engineering, and operations teams, design model evaluation experiments, improve operational processes, and create investigator insights for detecting financial crime across global transactions.

Own the global non-Google SEM portfolio across Bing, Yahoo Japan, and Naver. Develop campaign structures, testing frameworks, optimization playbooks, dashboards, automation, and AI-powered workflows. Partner with Product, Engineering, Data Science, and Operations to define technical roadmaps and solutions. Serve as a search marketing subject matter expert, influence external partner roadmaps, present performance recommendations to leadership, mentor colleagues, and build organizational capability.

Develop and improve quantitative models for investment strategies, conduct statistical analysis, and implement trading models. Requires strong analytical skills and relevant degree.

Design, build, test, and operate real-time streaming data solutions using Spark and Flink. Develop agentic AI workflows, tool integrations, orchestration capabilities, backend services, MCP systems, and secure APIs. Integrate AI tools with development platforms, apply large-scale telemetry processing, contribute to architecture decisions, and improve engineering and operational practices.

Leads product analytics for Wise’s Online Platforms vertical, owning growth and performance metrics, opportunity sizing, product discovery, forecasting, and strategic recommendations. Builds the analytics function, data foundations, reporting, and operating model while managing and developing product analysts. Partners with product, engineering, operations, commercial, and sales leaders to influence roadmaps, prioritize opportunities, and drive cross-functional action.

Trade a live EMEA short-term interest rate trading book across EUR/GBP rates and G10 FX swaps. Own electronic and manual market-making, develop systematic pricing algorithms, manage risk, and translate voice-trading intuition into model logic. The role requires strong quantitative and technical skills, trading judgment, collaboration with quant and developer teams, and hands-on Python coding for prototyping and debugging.

Leads site reliability engineering for Athena Core, improving application and platform reliability, scalability, observability, resiliency, and incident response. Establishes service level indicators, objectives, and error budgets; leads resiliency reviews and major-incident resolution; reduces toil; mentors engineers; and drives AI-assisted reliability workflows across CI/CD, testing, validation, and operational readiness while maintaining security and auditability.

Leads development of secure, scalable data platforms supporting batch, streaming, ML, and LLM workloads. Designs distributed data systems using Spark, Ray, Kafka, Iceberg, and OpenSearch; productionizes model training, deployment, monitoring, and lifecycle management; and builds governed LLM solutions. Provides technical leadership, code review, incident response, vendor evaluation, responsible AI guidance, automation, and mentorship across engineering teams.

Commodities Analysts generate commodity investment ideas through fundamental research and data analysis, focusing on modeling supply and demand and improving data quality.

Build, analyze, maintain, and optimize scalable data pipelines and complex data infrastructure. Develop ETL processes, data models, algorithms, and production software while working with large datasets and distributed batch processing. Collaborate with global engineering and product teams through analysis, prototyping, development, deployment, and maintenance. Apply data engineering, database, cloud, workflow orchestration, and software engineering practices in a dynamic agile environment.

Develop machine learning models and computer vision algorithms for photon-efficient, event-driven imaging in AR glasses. Responsibilities include tracking, depth estimation, SLAM, detection, probabilistic modeling, and novel imaging algorithms for ultra-low-light, high-temporal-resolution systems. The role requires collaboration with global hardware and software teams and emphasizes fast, reliable implementation in C++ and Python.

Develop and deploy computer vision and machine learning algorithms for photon-efficient, event-driven imaging in next-generation AR glasses. Responsibilities include tracking, depth estimation, SLAM, detection, probabilistic modeling, and ultra-low-light imaging. The role requires close collaboration with global hardware and software teams and focuses on creating fast, robust, and accurate solutions for wearable devices.

Lead product analytics for Wise’s Europe and UK regional expansion, partnering with product managers and analysts to define KPIs, assess product launches, conduct forecasting and experimentation, and influence data-driven decisions. Build and maintain data assets, identify opportunities to improve performance, and communicate actionable insights to technical and cross-functional stakeholders across a complex fintech environment.