Top Python Jobs in London

Build automated GRC solutions and maintain the GRC platform; architect AI governance for autonomous agents; support audit readiness (SOC 2, ISO 27001, PCI, FedRAMP) via automated drift detection and self-healing; and integrate security across Legal, People, Engineering, and Finance to enable developer-friendly compliance.

Conduct vulnerability scanning and in-depth analysis, triage and prioritize findings, produce remediation guidance, track remediation progress, and ensure processes and evidence meet DoD IL4 and FedRAMP compliance requirements while collaborating with engineering and compliance teams.

Lead technical customer-facing GenAI engagements for EMEA digital-native and startup customers. Design and productionize LLM solutions including RAG, agents, fine-tuning, evaluation, safety, and MLOps on Databricks. Build proofs of concept and reference implementations, advise customer roadmaps, partner with Product and Engineering, mentor field teams, and represent Databricks through technical content and executive briefings.

Lead technical pre-sales engagements for Databricks, demoing Spark and data/AI solutions, building architectures, authoring reference materials, and collaborating with account teams to design and deliver customised proofs-of-concept and workshops.

Provides technical leadership and owns cloud and solution architecture across agile delivery teams. Designs secure, scalable AWS solutions spanning applications, APIs, integrations, data, and infrastructure. Guides engineers, translates business requirements into technical solutions, makes architectural decisions, and supports CI/CD, containerization, testing, security, resilience, and operability. Requires significant AWS architecture experience, strong software engineering knowledge, stakeholder communication, and current UK SC security clearance.

Deliver end-to-end software implementation projects for RELEX’s Price & Promotions platform. Configure customer solutions, optimize forecasting and attribution parameters, implement business logic using SQL, Go, and Python, analyze large datasets, design integrations, support testing, and provide consulting to retail customers on pricing, promotions, forecasting, and automation. Collaborate with product and engineering teams while gathering requirements and addressing customer-specific business challenges.

Conduct machine learning research for autonomous-driving simulation realism. Responsibilities include contributing to existing projects, implementing research ideas, and running training and evaluation experiments. The role requires Python programming and deep learning experience with TensorFlow, JAX, or PyTorch. Preferred experience includes attention mechanisms, autoregressive architectures, diffusion for multimodal data, autonomous driving, and robotics.

Build data pipelines, integrations, and infrastructure for AI research workflows. Work directly with frontier AI labs and enterprise teams to clean and prepare datasets, automate experiments, support model-in-the-loop and human-in-the-loop quality control, and translate ambiguous research needs into scalable production systems for model training, evaluation, safety, interpretability, and alignment.

Execute physical and paper energy trades, develop arbitrage and proprietary trading strategies, hedge exposures, and maximise P&L within risk limits. Analyse market fundamentals, macroeconomic trends, freight, refining margins, inventories, and geopolitical risks. Negotiate supply and offtake agreements, collaborate with risk, finance, credit, and operations teams, maintain regulatory compliance, communicate market views to senior leadership, and mentor junior traders.

Designs and implements behavior planning algorithms for autonomous vehicles operating in structured, low-speed airport environments. Responsibilities include developing C++ and Python software, modeling multi-agent interactions, implementing decision-making and path-planning methods, testing in simulation and real-world scenarios, optimizing system performance, and collaborating with autonomy and engineering teams. The role requires expertise in behavior planning, probabilistic models, real-time navigation, debugging, profiling, and scalable software architecture.

Supports the Solutions COO team in managing a structured-products business, leading strategic and technology-focused initiatives, improving operational processes, automating MI and KPI reporting, managing budgets and costs, delivering platforms, coordinating regulatory projects, and serving as a liaison between business and control functions. The role also mentors junior staff and drives innovation, efficiency, and sustainable business growth.

Supports the Solutions trading and technology platform by delivering strategic and tactical initiatives, improving business processes, and driving automation. Manages project plans, technology change, regulatory coordination, operational risk, budgets, management information, KPIs, and stakeholder relationships. Translates business requirements into technology deliverables, supports derivatives trading capabilities, coordinates with Group Technology, and identifies opportunities to improve efficiency, compliance, profitability, and client solutions.

Build and maintain scalable full-stack applications using React, Redux, and Python backend frameworks. Design RESTful APIs and data-processing systems for high-volume network telemetry and time-series data. Develop AI-driven workflows that detect outages and automate network operations. Collaborate with product, platform, and cloud engineering teams on infrastructure, CI/CD, deployments, code quality, and system reliability. Mentor engineers and work directly with global telecommunications customers.

Technology interns spend 3–6 months embedded in teams developing software, DevOps, or data engineering solutions for Man Group’s investment and technology platforms. Responsibilities may include enhancing quantitative investment systems, integrating datasets, extending execution and order management systems, and supporting core infrastructure. Interns receive training, mentoring, and cross-functional exposure, complete technical assessments and interviews, and may be considered for a graduate technology programme.

Build and maintain revenue systems, integrations, automations, and AI-native workflows supporting Sales and Customer Success. Analyze data, perform root-cause investigations, improve revenue data hygiene, and measure results against KPIs. Collaborate with Sales, Partnerships, Marketing, Finance, and Engineering to translate business needs into scalable solutions. Drive operational efficiency, platform adoption, and automation across the revenue organization.

Owns revenue intelligence data models, governed datasets, LookML models, dashboards, and data quality processes. Integrates Salesforce and subscription billing data in BigQuery to report ARR, retention, churn, pipeline, and renewals. Partners with Sales, Customer Success, RevOps, Finance, and other stakeholders to define metrics, resolve data issues, and deliver trusted analytics. Applies software engineering practices to BI development and supports AI-assisted revenue analytics.

Maintains PostgreSQL research infrastructure, data ingestion processes, GitHub repositories, Python libraries, and automated analytical workflows. Productionises research code and collaborates with technology teams to improve investment data, modelling, and governance. Supports quantitative research, backtesting, testing, and implementation of systematic equity and fixed-income strategies using market, factor, fundamental, and ESG datasets, with opportunities to develop toward investment research and strategy design.

Develop automated QA strategies and evaluation frameworks for GenAI and agentic systems. Build Python-based tests across APIs, UIs, performance, prompts, and model behavior. Maintain regression suites, test datasets, and evaluation metrics covering accuracy, safety, relevance, consistency, and latency. Conduct adversarial testing for hallucinations and bias, support alerting and user acceptance testing, integrate tests into CI/CD pipelines, and document coverage and known issues.

Designs QA strategies, evaluation frameworks, quality metrics, and automated testing systems for GenAI and agentic applications. Develops Python-based end-to-end tests across APIs, UIs, performance, prompts, and regression scenarios. Performs adversarial testing for hallucinations, bias, and security issues; builds monitoring and alerting systems; maintains golden datasets; and establishes testing best practices for reliable, safe, and trustworthy AI features.

Develops quality assurance strategies and automated testing frameworks for GenAI and agentic applications. Responsibilities include Python-based end-to-end testing, prompt regression testing, API, UI, performance, security, and adversarial testing, plus evaluation metrics for accuracy, relevance, safety, consistency, and latency. The role also builds monitoring and alerting systems, maintains test datasets, and establishes QA best practices for AI features.

Develop automated QA strategies and evaluation frameworks for GenAI and agentic systems. Build Python-based tests across APIs, UIs, performance, prompts, and regression scenarios. Measure model accuracy, relevance, safety, consistency, and latency; curate test datasets and golden examples; conduct adversarial testing for hallucinations and bias; maintain CI/CD test integration, production alerting support, documentation, and user acceptance testing.

Lead the design, development, scalability, and operation of Ebury’s high-volume, multi-currency transactional platform. Own services from architecture through production, build resilient payment and funds-processing systems, collaborate with Product and Operations, mentor engineers, and ensure strong testing, observability, monitoring, and reliability across distributed global teams.

Designs, administers, and improves Linux-based HPC infrastructure supporting biomedical research, AI/ML, bioinformatics, data processing, and simulation. Responsibilities include managing compute, storage, networking, schedulers, containers, scientific software, monitoring, automation, security patches, disaster recovery, and workflow performance. The role supports researchers through troubleshooting, training, documentation, onboarding, stakeholder engagement, and development of reproducible computational environments and scalable research services.

Provide first-line data support to quantitative researchers and traders, troubleshoot data access and quality issues with data engineers, manage JIRA workflows, document data processes, onboard and train users, and help expand data coverage through live collection and backfills.

Lead AI-driven operational transformation across Legal, People, and FP&A. Identify workflow inefficiencies, design end-to-end solutions, and personally prototype and deploy AI agents, automations, integrations, and internal tools. Evaluate build-versus-buy decisions, advise on technology stacks, and ensure solutions include security, privacy, reliability, monitoring, auditability, human oversight, and change management. Partner with frontline teams, executives, and engineers to deliver measurable, maintainable internal products.