Top Python Jobs in London

Serve as a customer-facing technical advisor for Snowflake, partnering with sales teams and channel partners throughout the sales cycle. Present solutions to technical and executive audiences, conduct demos and proofs of concept, design architectures, develop technical champions, and solve data-related business problems. Collaborate with Product, Engineering, Marketing, and implementation partners while staying current on Snowflake, cloud, data, and AI technologies.

Partners with account sales teams, channel partners, and customers to solve complex data challenges and drive Snowflake evaluations. Presents technology to technical and executive audiences, delivers demos and proofs of concept, develops technical champions, designs solutions, and supports implementation. The role requires data architecture, analytics, cloud technology, and SQL expertise, with preferred experience in Python, modern data tooling, AI, machine learning, and financial services.

Partners with sales teams and customers to identify needs, lead winning sales cycles, deliver executive and technical presentations, demonstrate Snowflake solutions, support enterprise proofs of concept, and help close large deals. The role requires expertise in data platforms, cloud technologies, generative AI, machine learning, LLM ecosystems, data governance, data modeling, and data engineering, while collaborating with Product, Engineering, Marketing, and channel partners.

Develop efficient generative world models and planners for closed-loop autonomous-driving simulation. Responsibilities include designing diffusion or transformer-based models, enabling interactive agent simulation, optimizing inference latency and compute efficiency, defining evaluation metrics, integrating models into training and evaluation workflows, measuring sim-to-real performance, mentoring researchers, and contributing to technical roadmaps and publications.

Develop performant, reliable, and well-tested software for a high-performance financial exchange. Work across backend, frontend, cloud, data, and testing systems, including distributed core Java, Kafka, MySQL, JavaScript, Vue.js, Kubernetes, and Python. Collaborate through pair programming, team rotations, continuous integration, and continuous delivery while contributing to greenfield projects, performance-critical components, blockchain integrations, and developer-experience improvements.

Designs, installs, configures, upgrades, patches, and maintains Sybase ASE and IQ databases across Linux and Unix platforms. Responsibilities include performance tuning, backup and recovery, security administration, high availability, replication, disaster recovery, bulk loading, capacity planning, automation, data warehouse support, cloud and cross-platform migrations, and database decommissioning. Supports production issues through on-call rotations and collaborates with application, development, and infrastructure teams in large-scale banking and financial services environments.

Build and support Nivoda’s go-to-market infrastructure through integrations, event flows, automations, and services. Translate stakeholder needs into reliable technical solutions across Salesforce, GTM tools, Snowflake, and enrichment systems. Apply APIs, webhooks, queues, workflows, testing, monitoring, version control, and safe deployment practices while handling failures, retries, duplicates, and recovery documentation.

Build and maintain scalable Python libraries, tools, and infrastructure enabling machine learning teams to train, evaluate, and deploy models at scale. Develop abstractions for distributed training, data loading, inference, checkpointing, and evaluation; support large GPU clusters and cloud environments; optimize multimodal data pipelines; and improve reliability through architecture, testing, observability, documentation, and maintainability.

Lead AI safety projects for frontier labs, developing evaluation frameworks, scientific experiments, and supporting software architectures. Mentor technical teams, shape project scope and feasibility with commercial partners, advance AI evaluation research, and ensure rigorous scientific and technical standards throughout delivery.

Owns an EMEA enterprise territory and full SaaS sales cycle, from prospecting through proposal, proof of value, negotiation, and contract closure. The role develops new revenue, maintains accurate Salesforce pipeline and forecasts, engages VP and C-level buyers, builds partner-generated pipeline, and develops customer advocates. It is London-based, requires four office days weekly, and involves approximately 25% travel across the UK and wider EMEA.

Own the realtime and voice layer of Hopper’s AI travel assistant, including telephony integrations, speech pipelines, model orchestration, and performance. Build full-stack features with React, TypeScript, Scala, and Python on GCP, supporting multi-tenant enterprise deployments. Develop safety, compliance, observability, alerting, and incident-response capabilities, while maintaining SLAs and revenue-critical systems. Mentor engineers and collaborate across product, design, and operations.

Lead a DevOps team responsible for building, scaling, securing, and optimizing ML and GenAI infrastructure. Define cloud infrastructure roadmaps, automate provisioning, architect MLOps and LLMOps pipelines, deploy LLMs to production, and manage AI infrastructure budgets through FinOps practices. Implement resource-efficiency measures, observability, incident response, data governance, and security controls while collaborating with Data Science and Engineering leaders.

Lead media measurement and campaign analytics for global clients (JLR), design experiments and measurement frameworks (lift studies, MMM, MTA), deliver actionable insights, manage stakeholder relationships, support commercial scoping and global rollouts, and mentor junior analysts.

Serve as a senior analytics partner to underwriting and related teams, translating commercial questions into analyses, dashboards, and actionable insights. Deliver complex analytics workstreams, govern Power BI development and releases, apply SQL and data modeling standards, and support automation and AI-enabled workflows. Coach analysts, conduct peer reviews, collaborate with Data Engineering, and contribute to Agile planning, stakeholder engagement, and external data propositions.

Designs, implements, audits, and optimizes cloud security solutions for clients across multiple industries. Responsibilities include securing AI tools and applications, designing identity and access management, deploying XDR and cloud SIEM/SOAR solutions, assessing cloud security posture, producing technical documentation, presenting recommendations, and collaborating with customers and internal teams. The role requires Azure and Microsoft security expertise, customer-facing communication, and occasional travel to client sites.

Supports the design, implementation, testing, and improvement of valuation models for derivatives, structured products, swaps, fixed income, securitisations, and other complex financial instruments. Performs valuation analyses, Monte Carlo simulations, market data validation, output reviews, technical reporting, and client deliverables. The role also contributes to automation of valuation processes and applies quantitative methods from finance, mathematics, statistics, computer science, and economics.

Develop and maintain scalable VFX production tools, pipelines, and workflows while providing technical support to artists, coordinators, and producers. Troubleshoot pipeline, data-flow, review, and transfer issues; maintain Flow Production Tracking; document workflows and issues in JIRA; and collaborate with technical teams across London and Los Angeles.

Leads independent investment valuation reviews, price verification, and valuation governance across fixed income, derivatives, private credit, structured products, real estate, and other illiquid assets. Reviews methodologies, models, assumptions, and market data; investigates control exceptions; and improves valuation processes, systems, data quality, and reporting. Supports liquidity modeling, stress testing, regulatory and audit activities, financial reporting, and senior governance committees.

Build, deliver, and operate AI-focused DevOps environments across hybrid infrastructure, Azure, and AWS. Develop RAG and data pipelines, MLOps workflows, AI agents, GPU workloads, infrastructure automation, and containerized platforms. Support live, business-critical systems while improving scalability, reliability, observability, and standardization. Collaborate across teams, modernize infrastructure, and implement emerging AI and cloud technologies.

Lead platform engineering strategy and hands-on delivery across highly available cloud infrastructure, CI/CD, developer tooling, security, observability, and incident management. Establish standards for AI-assisted software development, validate AI-generated code, measure productivity and quality, and influence engineering, product, and quantitative teams. Mentor engineers and drive cross-team initiatives focused on scalability, resilience, compliance, and operational excellence.

Own end-to-end development of scalable full-stack experiences for a real-money prediction and trading platform. Design and implement React, Next.js, TypeScript, and backend services; build experimentation, observability, and deployment capabilities; conduct code reviews; collaborate cross-functionally; and establish effective AI-assisted development standards while helping shape an early-stage product.

Leads platform engineering initiatives across AWS cloud infrastructure, Kubernetes, CI/CD, GitOps, Infrastructure as Code, observability, and developer tooling. The role architects reliable and scalable platforms, improves developer productivity and operational excellence, partners with application teams, leads cross-team technical programs, mentors engineers, and participates in on-call rotations.

Designs and maintains highly available cloud-native infrastructure, CI/CD pipelines, developer tooling, platform security, and observability systems. The role partners with engineering and product teams to deliver scalable solutions, leads incident response, evaluates AI-generated code for security and architectural risks, and mentors engineers. Candidates will use AI coding collaborators, infrastructure-as-code, Java and Python, and modern cloud platforms to improve developer productivity and operational reliability.

Build and operate production data pipelines using Python, SQL, Airflow, Snowflake, and Databricks. Implement ingestion sources, DAGs, schemas, monitoring, catalog registration, reverse ETL, and governance controls. Investigate pipeline failures, perform lineage analysis, review code, identify downstream risks, and support data quality, security, and access controls. Collaborate with stakeholders, clarify requirements, document escalations, and mentor junior data engineers.

Manage, support and enhance global network infrastructure across on-premises, colocation and cloud. Design and build network products, maintain network security (next-gen firewalls), implement BAU changes, develop IaC and SRE-driven network automation, support cloud networking (Azure/AWS), run data centre operations and manage third-party vendors.