Top Python Jobs in London

Leads research and production development of generative AI and large language model systems for cybersecurity. Responsibilities include defining AI research strategy, developing novel reasoning and summarization approaches, selecting model architectures and deployment strategies, building large-scale production systems, mentoring scientists, establishing evaluation standards, and guiding cross-functional technical initiatives. The role also represents the company through publications, speaking engagements, and technical thought leadership.

Lead and mentor cross-functional engineering teams to deliver scalable, resilient cloud-native systems. Partner with product to define technical solutions, manage technical debt, hire and grow engineers, and drive engineering best practices. Hands-on leadership with strong frontend and distributed systems experience.

Architect and develop complex C++ and SystemC hardware models, firmware, software, and QEMU-based emulation platforms. Debug models and Python processing code, support model-driven hardware design flows, validate implementations, and collaborate across teams to improve development methodologies. The role also provides technical leadership and mentorship to engineers adopting model-first development.

The Data Analyst will analyse complex datasets, develop dashboards and reports, translate stakeholder requirements into data-driven solutions, and support analytical models and AI-enabled capabilities. The role involves collaborating with engineers, architects, and business analysts; ensuring data quality and governance; participating in Agile delivery; presenting insights; and supporting UX/UI for digital tooling within a secure Defence programme.

Develop optimization models, machine learning algorithms, and statistical solutions for global supply chain challenges, including network design, inventory, forecasting, and transportation. Clean and analyze large datasets, build production-ready solutions in Python or R, create dashboards, and communicate actionable insights. Collaborate with cross-functional technical and business teams to improve cost, service performance, and sustainability.

Build and own ElevenLabs’ analytics transformation and metric layers using dbt and SQL. Define certified KPIs for product, finance, and company-wide reporting; establish modeling, testing, CI, documentation, and data-quality standards; collaborate with Data Engineering and stakeholders to create trusted, reusable data products and support AI-agent data use cases.

Own and improve scalable platform components across their lifecycle, contributing to architecture, reliability, performance, automation, observability, and production readiness. Build infrastructure and CI/CD solutions using AWS, Terraform, containers, and orchestration technologies. Participate in incident response and on-call rotations, mentor engineers, uphold technical standards, and collaborate with product and engineering leaders. The role also emphasizes distributed systems, security, operational excellence, and using AI tooling to improve productivity.

Build and operate backend pricing systems for real energy contracts. Responsibilities include designing the Pricing API, consolidating pricing logic, improving quote speed, implementing error handling and observability, creating alerting, explaining pricing failures, and supporting live incidents. The role requires production Python backend experience, FastAPI, SQL, data-heavy systems, end-to-end project ownership, and AI-assisted development workflows.

Lead a team of 7–8 engineers building ENSEK’s Flex cloud-native energy platform. Responsibilities include hiring, coaching, sprint planning, technical decision-making, architecture, engineering quality, CI/CD, testing, observability, incident response, operational excellence, and cross-functional collaboration with Product, UX, Data, and SRE. The role also contributes to team-model evolution and broader engineering strategy while ensuring reliable, commercially valuable product delivery.

Own Quince’s international forecasting and replenishment architecture, combining classical forecasting, machine learning, and AI agents. Build prototypes and analytical tools in Python, SQL, and Streamlit; partner with data and engineering teams to productionize successful solutions. Improve forecast accuracy, reduce stockouts, automate planning workflows, support new-market launches, and translate between planners, engineers, and leadership. Establish trusted human-machine decision processes and continuously improve planning systems across international markets.

Own finance-focused data science and analysis, including revenue and ARR reconciliation, cohort economics, pricing experiments, forecasting, and scenario modeling. Partner with Analytics Engineering to maintain certified finance KPIs and ensure data quality across billing and revenue systems. Translate ambiguous questions from FP&A, RevOps, and leadership into reusable analyses that support planning, board reporting, pricing, and IPO readiness.

Leads hands-on software architecture, development, deployment, and issue resolution for strategic customer projects. Drives AI innovation, Azure and platform resiliency, security, observability, performance, and operational improvements. Partners with executives, customers, engineering, and product teams to define and deliver strategic programs. Develops tools, shares technical best practices, and supports Microsoft Fabric and GenAI solutions, including governance, automation, testing, and responsible AI controls. Requires frequent worldwide customer travel and regular engagement in Redmond.

Graduate software engineers will develop open-source and commercial software across the Linux stack, from firmware, kernels, and drivers to desktop applications, containers, clouds, and Kubernetes. Responsibilities include writing resilient, performant code, contributing to product roadmaps, engaging with users and open-source communities, addressing customer issues, and developing secure software. The role is globally remote with twice-yearly international team sprints and emphasizes mentorship, collaboration, and continuous technical growth.

Provides enterprise SOC/MDR security operations support focused on QRadar administration and engineering, log source integrations, troubleshooting, use case development, content tuning, workflow maintenance, and automation. Supports integrations such as CrowdStrike auto-isolation and develops Python scripts for existing automation requirements. Requires extensive hands-on QRadar expertise and significant IT experience.

Lead the design, development, and operation of scalable data pipelines using Databricks and Azure Synapse. Administer Azure data platform services, Databricks workspaces, security controls, networking, and governance. Manage infrastructure as code with Pulumi or similar tools, build CI/CD automation, monitor platform health, resolve incidents, and mentor junior colleagues while maintaining secure and reliable cloud data environments.

Own the analytical layer for autonomous-driving model evaluation and release decisions. Analyze simulation and on-road experiment data, improve performance metrics and scoring methods, identify measurement gaps, apply statistical rigor, and translate investigations into actionable recommendations. Partner with Data Science, Validation, Product, engineering, and OEM teams to strengthen evaluation coverage, ground truth, quality investigations, and weekly model-release feedback loops.

Designs, implements, and operates Era4’s enterprise observability platform across AI infrastructure. Responsibilities include managing telemetry collection, Grafana-based monitoring, Kubernetes integrations, alerting, dashboards, distributed tracing, multi-tenant controls, object-storage-backed retention, and OpenTelemetry integrations. The role also develops Infrastructure-as-Code and GitOps automation, supports incident detection and root-cause analysis, validates resilience and disaster recovery, and establishes observability standards, SLIs, SLOs, security controls, and operational governance.

Designs, develops, and maintains scalable data structures, models, and automated pipelines for analytical and reporting needs. Integrates multiple source systems, transforms data into reusable datasets, monitors data quality, and implements validation and reconciliation processes. Collaborates with analysts and stakeholders to translate reporting requirements into datasets, maintains data documentation and lineage, and improves automation and efficiency. This is a UK-based remote role with occasional onsite attendance.

Lead global second-line oversight of credit, FX, and counterparty risk across Airwallex’s products and legal entities. Own risk frameworks, appetite, limits, governance, portfolio monitoring, underwriting challenge, escalation, loss mitigation, and new-product risk assessments. Partner with senior leaders, regulators, auditors, banking partners, and risk committees while overseeing exposures across payments, cards, FX, treasury, settlement, and banking activities.

Paid 6-12 month research internship creating and experimenting with ML models across vision, language, and audio to support game development, own data analysis/creation, and help deploy models at scale while collaborating with research scientists and engineers.

Lead end-to-end LogicMonitor implementations for new and existing customers. Conduct discovery, design, and deployment sessions; optimize configurations; automate tasks using APIs and scripting; develop custom integrations; and promote customer adoption. Collaborate with Professional Services, Customer Success, Support, Training, Product, Development, and Sales teams. Provide subject-matter expertise, technical feedback, and occasional monitoring engineering support. Travel 10–20%.

Leads end-to-end development and production deployment of machine learning, generative AI, and agentic solutions for payments and banking. Responsibilities include problem framing, experimentation, evaluation, MLOps, LLMOps, governance, monitoring, scalable cloud architecture, security, and systems integration. The role establishes reusable AI capabilities, partners with cross-functional stakeholders, mentors technical teams, and communicates model outcomes and operational tradeoffs to technical and non-technical audiences.

Own Perk’s go-to-market engineering strategy, architecture, tooling, roadmap, and commercial outcomes. Build production-grade Clay workflows, Salesforce automations, enrichment systems, orchestration logic, and agentic AI solutions using code and modern GTM technologies. Automate prospecting, selling, and account-management processes across global teams. Lead a senior international team, establish engineering standards, partner with revenue leadership, and quantify business impact through improved productivity and funnel performance.

Build, maintain, and monitor live trading infrastructure; develop research platforms and analytics tools; and collaborate with quantitative researchers to productionize trading strategies. The role involves greenfield development, system enhancement, refactoring, and exposure to trading and research platforms. Candidates should have strong software engineering, numerical reasoning, and problem-solving skills, with proficiency in a modern programming language and interest in quantitative research, machine learning, cloud platforms, and emerging development technologies.

Lead Site Reliability Engineer responsible for maintaining production reliability, availability, scalability, and performance. Duties include incident response, post-mortems, SLO and SLI management, Kubernetes administration, automation, capacity planning, performance optimization, documentation, and on-call support. The role partners with development and operations teams to improve service reliability and engineering practices.