Top Python Jobs in London

Identify and evaluate audiovisual generative AI technologies, prototype proof-of-concept implementations, test research developments, and build scalable ComfyUI workflows. The role involves model training and inference, dataset management, pipeline integration, hyperparameter tuning, collaboration with research, product, and creative teams, presenting findings, and training artists. It is remote across EMEA.

Oversee daily and monthly P&L reporting, reconciliations, valuations, pricing, and product setup for OTC derivatives, with emphasis on emerging markets and delta-one strategies. Partner with trading, fund accounting, portfolio management, operations, and fund administrators to ensure accurate T+1 and monthly reporting. Investigate valuation differences, explain results to stakeholders, and manage high-volume data in a fast-paced environment.

Build and implement quantitative risk, portfolio, trading, and data models across equity and fixed-income products. Collaborate with quantitative analysts, portfolio managers, risk teams, and technology partners. Apply Python, database technologies, forecasting, statistical modeling, and diverse data sources while managing multiple projects independently and collaboratively.

Designs, trains, evaluates, and productionizes machine learning models and AI systems using complex public-sector datasets. Builds reproducible ML pipelines, schema-aware data flows, LLM and RAG workflows, NLP models, and containerized services integrated with the OneView platform. Leads technical delivery for client projects, troubleshoots production issues, configures modeling outputs, mentors colleagues, and contributes reusable engineering components. The role is hybrid in London with occasional client travel and is a 12-month maternity leave cover.

Conduct quantitative analysis of live and historical digital-asset market data, develop and backtest trading signals under realistic execution constraints, support cross-exchange arbitrage and basis strategies, build production-quality research tooling, and present findings to traders and researchers.

Five- to six-month data engineering internship supporting quantitative research and trading platforms. The intern may work on data acquisition, large-scale datasets, data stores, APIs, production datasets, and real-time or batch data infrastructure. Responsibilities emphasize reliability, performance, scalability, and collaboration with researchers, traders, and engineers. Candidates should have computer science fundamentals, Python experience, structured problem-solving skills, and clear communication. SQL or NoSQL knowledge, front-end experience, and financial markets interest are preferred.

Build scalable data pipelines, data models, feature stores, and cloud-native data applications supporting machine learning workloads. Partner with Machine Learning Engineers and Data Scientists to create reliable datasets, maintain production pipeline quality and observability, and support batch and real-time data systems. The role uses Python, SQL, Spark, Airflow, AWS, CI/CD, and modern data engineering technologies.

Deliver client-facing renewable energy advisory services for onshore wind assets, including due diligence, owner’s engineering, lifetime extension, repowering, and decommissioning assessments. Manage projects, budgets, contracts, reports, proposals, and client communications. Evaluate technical and commercial aspects of renewable infrastructure, support business growth, mentor colleagues, and identify relevant technology or regulatory developments. Travel to client meetings and project sites in the UK and globally.

Provides technical leadership and solution architecture for scalable, secure, cloud-native software platforms. Responsibilities include defining technology roadmaps, designing microservices and APIs, leading full-stack development with Python, SQL, AWS, and React, driving DevOps and CI/CD practices, overseeing delivery, mentoring engineers, and ensuring quality, security, observability, and stakeholder alignment.

Build and deploy a modern AI-integrated application on GCP during a 12-week contract. Develop React/TypeScript frontends and Python/FastAPI backends, deploy services with Cloud Run and Cloud Run Jobs, integrate Vertex AI Gemini models, manage Firestore and BigQuery data, configure enterprise SSO with IAP and Microsoft Entra ID, and maintain Azure DevOps CI/CD pipelines.

Investigate fraud and insider-threat cases from initial signal through resolution. Gather and analyze logs, transactions, behavioral signals, and other evidence; triage alerts; reconstruct events; document findings objectively; maintain evidence chain of custody; and collaborate with Detection & Response, Legal, and HR. The role also contributes to investigation playbooks, detection improvements, and fraud and insider-risk prevention.

As a Quantitative Research Analyst Intern, you will model markets, develop algorithms, and conduct statistical analysis to enhance trading strategies.

Lead and mentor a cross-functional engineering team building growth-critical platforms, AI-driven tools, automations, and user engagement systems. Partner with Product and Design to prioritize work, guide architecture, improve processes, and deliver reliable production features. The role combines people leadership with hands-on backend software development, technical decision-making, stakeholder communication, and team enablement across distributed time zones.

The Staff Software Engineer will lead cross-functional teams to deliver impactful features for the Flights platform, enhancing customer experiences while managing complex technical initiatives.

As a Software Engineer, you will develop backend services for AI applications, optimize cloud infrastructure, and manage production-level deployments.

Lead CRM analytics for Personal and Business segments: design measurement frameworks, run campaign and lifecycle analyses, apply A/B and incrementality testing, build segmentation models, maintain dashboards, ensure data quality, and partner with CRM, Product, and Data teams to optimise customer engagement and retention.

The Senior Site Reliability Engineer will automate processes, collaborate across teams, and enhance service resilience in a cloud-native environment, focusing on system scalability and best practices.

The Lead Value Engineer is a trusted advisor to customers, driving their value journey through analytics, process improvement, and stakeholder engagement, particularly in Finance and Supply Chain.

The Principal Enterprise Architect will lead solution architecture and cloud strategy, engaging with C-level executives, driving innovation, and collaborating across teams to support sales and customer expansion.

Administer MT4/MT5 trading environments, configure instruments, pricing, swaps, margins and trading sessions, and monitor execution quality, liquidity and platform health. Investigate slippage, rejections and other execution incidents; support risk implementations; produce P&L, reconciliation and exception reports; manage vendor and connectivity escalations; maintain operational logs and audit trails; and test or automate dealing tools. The role requires shift flexibility and close collaboration with Risk, Technology, Compliance and Sales.

Leads client engagements delivering data, analytics, automation, and AI solutions for complex programmes and business operations. Responsibilities include defining requirements, designing data processes and pipelines, resolving data quality issues, providing technical delivery assurance, applying generative AI and LLM solutions, managing stakeholders, supporting proposals, and mentoring teams. The role also contributes to reusable methods, documentation, innovation, and client relationship development.

Deliver live and online technical training and workshops for clients and partners; build and maintain course content, video tutorials, and certification assessments; translate product features into usable learning materials; support partner enablement and maintain course health and documentation.

Design, build, and maintain scalable data pipelines and platform services to support analytics, ML, and product teams. Implement infrastructure-as-code (Terraform) and Kubernetes-based deployments, develop data services/APIs, and ensure data quality, observability, security, and compliance. Partner with cross-functional teams, document systems, and continuously improve performance and reliability.

Lead end-to-end deployment of frontier AI models for strategic customers, from discovery and system design through production rollout. Build full-stack systems, contribute production code, guide customer adoption, manage delivery trade-offs, and codify reusable tools and playbooks. Partner with customer engineering, Product, Research, Security, GRC, Partnerships, and GTM teams while providing feedback to improve models and product roadmaps. Professional fluency in Spanish and English is required, with travel up to 50%.

Designs, builds, and validates bespoke security solutions and automation using enterprise AI tools. Performs STRIDE threat modeling, vulnerability analysis, technical risk assessments, remediation verification, and security control mapping. Ensures compliance with ISO 27001, NIST standards, and the EU Cyber Resilience Act. Develops security architecture documentation, maintains sandbox labs, verifies encryption, access controls, MFA, and logging, and supports pre-sales security tenders and customer evaluations.