Top Python Jobs in London

Build and scale reliable, API-driven global payment systems integrating banks and payment gateways. Translate product and design requirements into maintainable, tested components; improve performance, accessibility, and usability; contribute to shared libraries and code reviews; and support feature operational health. Collaborate with product, business, operations, design, and backend teams while driving technical decisions, architectural improvements, and engineering practices for large-scale financial infrastructure.

Leads strategic analytics consulting engagements from problem framing through actionable recommendations. Responsibilities include scoping analytical work, managing client delivery, governance, budgets, risks, and quality; analyzing credit risk, scorecards, portfolios, segmentation, and bureau data; presenting findings to senior stakeholders; supporting commercial opportunities; and coaching analysts and consultants.

Embeds with hardware engineering teams to build agentic workflows and AI skills that perform engineering tasks, including requirements checks, test-plan analysis, and issue investigation. Demonstrates value to customers, identifies reusable patterns, and translates customer needs into product capabilities. Requires strong Python and data skills, customer-facing communication, modern AI coding-agent experience, and willingness to travel. Hardware, test, controls, forward-deployed, solutions engineering, and security-clearance experience are advantageous.

Develop and deploy predictive and prescriptive models, AI/ML roadmaps, MLOps practices, and IoT analytics for infrastructure and environmental projects. Analyze geospatial, operational, environmental, sensor, and telematics data; build forecasting, optimization, anomaly detection, and streaming inference solutions. Collaborate with engineering teams, mentor junior staff, communicate insights to diverse audiences, and support data-driven business decisions.

Build and deploy production software for complex customer data, machine learning, and application environments. Own system design, deployments, integrations, backend services, APIs, data workflows, and product functionality end to end. Work directly with customers and engineering teams, debug production issues, create reusable tooling, communicate technical trade-offs, and feed deployment insights into product and engineering roadmaps.

Own production system reliability, incident response, observability, automation, and recovery workflows. Build self-healing capabilities, diagnostic tooling, runbooks, and golden-path operational workflows while partnering with platform and engineering teams on CI/CD, infrastructure resilience, SLOs, and reliability improvements. The role combines hands-on production support with development of automation that reduces toil, accelerates recovery, and prevents recurring failures.

Forward Deployed Engineers embed with strategic clients to design and deliver production-grade technical solutions. Responsibilities include building Python applications, complex SQL queries, data pipelines, API integrations, cloud and data-platform solutions, and AI/ML prototypes. They lead technical discovery, architecture, implementation, debugging, workshops, and operationalization while translating client mission needs into scalable product improvements. The role requires strong communication, ambiguity management, and up to 50% travel.

Support ML engineering teams running production training and inference workloads across Kubernetes, cloud, Linux, and GPU infrastructure. Diagnose distributed PyTorch, CUDA, NCCL, networking, storage, scheduling, and performance issues; analyze observability data; advise customers during incidents; and improve reliability through tooling, automation, documentation, runbooks, and operational processes. The role is hybrid in London, requires at least two office days weekly, and supports EMEA shifts.

Manage an engineering team building reusable infrastructure platforms and core distributed systems. Architect highly available services, review designs, plan roadmaps, optimize cloud costs, and enforce deployment standards across AWS and GCP. Lead planning, retrospectives, on-call practices, and reliability initiatives involving SRE, CI/CD, chaos engineering, and incident analysis. Develop engineering strategy, mentor senior engineers, and influence platform decisions across product teams.

Manage brand supply chain and e-commerce fulfillment operations across multiple commerce channels. Responsibilities include catalog and order management, sales forecasting, inventory optimization, multi-channel fulfillment, promotional planning, defect resolution, and client recommendations. The role serves as a subject matter expert in packaging, fulfillment, supply chain optimization, and related technologies while using data to improve profitability and operational performance.

Drive AI-led transformation across Legal, People, and FP&A by identifying workflow pain points, mapping end-to-end processes, and building reliable AI agents, automations, integrations, and internal tools. Advise on build-versus-buy decisions and technology stacks while implementing security, privacy, compliance, monitoring, human oversight, evaluation, and audit controls. Partner with frontline teams, executives, and engineers to deliver and continuously improve internal AI products.

The Infrastructure Engineer will oversee and support virtualisation, storage, and backup systems, troubleshoot issues, and implement updates and automations.

Leads eDiscovery consulting engagements, including client development, litigation data collection strategies, forensic coordination, data reduction, review technology selection, workflow design, project finances, and delivery oversight. Builds relationships with legal practitioners, generates revenue through cross-selling, manages project timelines and quality, mentors junior staff, and supports recruiting. Requires eDiscovery consulting experience, familiarity with EDRM and review, forensic, database, email, and systems technologies, plus willingness to travel nationally and internationally.

Design, build, test, deploy, and operate secure, scalable production software and services. Partner with customers and stakeholders to translate business needs into technical solutions, lead technical workstreams, apply engineering best practices, and deliver reusable systems. Collaborate with data science, product, design, and security teams while using AI-enabled tools and data-driven experimentation to solve complex customer challenges.

Lead data science for Trainline’s B2B product organization by uncovering growth opportunities, shaping product roadmaps, defining success metrics, supporting experimentation, and driving data-informed decisions. The role requires communicating complex analyses to senior stakeholders, evaluating product engagement, navigating ambiguous datasets, building predictive models, and using visualization and automation tools to deliver measurable business impact.

Develop, validate, and deploy computer vision and machine learning algorithms for clinical decision support using imaging and sensor data. Own projects from messy data and modeling through rigorous evaluation and production integration. Collaborate with hardware, software, medical, and clinical research teams, apply classical and deep learning methods, support regulatory readiness, deliver production-quality Python code, and mentor colleagues.

Design and implement generative and predictive models of cellular behavior using biological and single-cell perturbation data. Develop models for generalization, counterfactual prediction, causal reasoning, and experimental design. Collaborate with experimental biology teams to validate computational hypotheses, evaluate mechanistic fidelity, and guide real-world interventions. Communicate findings across interdisciplinary teams while contributing to a matrixed, collaborative research environment.

Leads the design, implementation, and delivery of enterprise Microsoft Azure AI and generative AI solutions. Develops RAG, vector search, AI agent, and LLM applications integrated with enterprise data and APIs. Establishes AI security, governance, monitoring, and responsible AI practices while leading technical teams and mentoring engineers. Engages senior clients, translates business needs into technical solutions, supports proposals and architecture, and drives large-scale data and AI programs and thought leadership.

Design and deliver enterprise Microsoft Copilot, AI agent, Generative AI, and data architecture solutions. Integrate AI with Microsoft 365, Dynamics 365, Power Platform, Dataverse, APIs, and enterprise data. Lead technical design, development, testing, deployment, governance, security, and production support. Manage delivery plans, risks, quality, and timelines while mentoring engineering teams. Partner with clients and senior stakeholders, support proposals and transformation initiatives, and provide architectural thought leadership.

Lead teams delivering modern quality engineering and test automation solutions for clients. Define testing strategies, remain hands-on with automated testing and coding, and influence technical direction. Use object-oriented programming, GenAI, AI-assisted coding tools, and cloud testing environments. Mentor engineers, contribute to quality engineering communities, adapt to varied technology stacks, and travel to UK client sites as needed.

Deliver supply chain and AI consulting engagements through diagnostics, spend analysis, demand and inventory modeling, network analysis, data modeling, and AI solution development. Support client workshops, stakeholder interviews, recommendations, visualizations, operating models, and implementation roadmaps. Work with supply chain, procurement, ERP, analytics, and decision intelligence platforms while contributing to thought leadership and reusable assets.

Develop ultra-high-performance Java software for pricing, execution, and risk management in an algorithmic trading platform. Collaborate with quantitative researchers to implement scalable, highly available models and design distributed systems supporting 24x7 trading operations. Responsibilities include server-side development, software releases during live trading, and solving performance, reliability, and high-availability challenges.

Leads the 2D VFX department, supervising compositors, creative and look development, shot quality, client reviews, production workflow, bidding, and pipeline development. Provides feedback, assigns work, resolves technical and artistic compositing challenges, coordinates with production and other VFX departments, and supports on-set VFX supervision. The role also contributes to long-term team development and stereoscopic project workflows.

Own marketing performance analytics across paid, affiliate, influencer, and CRM channels. Develop attribution frameworks, analyze customer journeys and subscription metrics, build Tableau dashboards, and create scalable dbt data models. Use SQL, Python, or R for cohort analysis, forecasting, predictive modeling, and marketing mix modeling. Translate complex findings into actionable recommendations for senior stakeholders and collaborate across marketing, product, medical, finance, and data teams.

Own the analytical foundation for a multi-site labour optimisation programme. Analyze labour productivity, identify efficiency opportunities, improve reporting, support demand-to-labour modelling, evaluate forecast accuracy, and measure scheduling changes. Partner with Operations, Finance, Data Science, Business Partners, and General Managers to implement improvements while protecting service and member experience. Build practical BI tools using operational, scheduling, attendance, and payroll data.