Top Python Jobs in London

Build and operate DV's model layer: fine-tune and distill open-weight models, run on-prem inference infrastructure on Kubernetes, implement a model gateway routing across providers, evaluate model quality/cost/latency, manage GPU provisioning and utilization, and define tooling for model selection and production regression testing.

Design, build and optimize scalable AWS-based data pipelines and ETL processes (batch and near-real-time) using Python, SQL, Airflow, Glue and Redshift. Improve performance, reliability and cost efficiency, implement monitoring/alerting, support governance, security and compliance, collaborate with architecture and analytics teams, and mentor colleagues.

Partner with account teams to design and present customised portfolio analyses and liability-aware investment solutions (LDI/CDI) for institutional clients, especially pension schemes. Produce thought leadership, leverage quantitative modelling and AI-enabled tools, and act as a trusted advisor to support business development and client servicing across fixed income, multi-asset and private markets.

Design, build, and deploy production-grade agentic AI systems: multi-agent orchestration, RAG pipelines, LLM provider integration, LLMOps (eval harnesses, prompt versioning, observability), cloud-native deployment, and reusable patterns while embedding with client engineering teams to measure and improve agent accuracy, latency, safety, and cost.

Design, build, and deploy production-grade multi-agent AI systems for enterprise clients. Own RAG pipelines, multi-LLM integration, LLMOps (eval, prompt governance, observability), orchestration frameworks, and lead client engineering engagements and engineering teams.

Build and maintain Dialpad's native Salesforce integration and other integrations, design architecture, write clean modular code with unit tests, participate in code reviews, mentor engineers, support ETL pipelines, and contribute to Agentic AI initiatives to enable real-time automations and data flows.

Join the Core backend team to develop resilient platform infrastructure powering B2C, B2B and API features. Build and refine critical flows for OCPI charging sessions, evolve tariffs/pricing logic, improve observability and scalability, and collaborate cross-functionally to deliver robust technical solutions.

Lead design and implementation of high-performance agent runtimes, backend services, and self-hosted model/agent infrastructure. Build low-latency execution systems, real-time data pipelines, telemetry loops, CI/CD for zero-downtime deployments, and ensure fleet reliability on AWS/EKS.

The Senior Software Cybersecurity Engineer analyzes software for security, performs threat modeling, leads security efforts, mentors teams, and integrates security throughout the development lifecycle.

Lead budgeting, forecasting, and variance analysis while building AI-driven financial models, scenario planning, KPIs, and dashboards. Automate FP&A processes, deliver insights to senior leaders, and collaborate with cross-functional teams to improve forecast accuracy and strategic decision-making.

Design, implement, and optimize AI-driven solutions across the claims lifecycle (intake, investigation, adjudication). Build ML models for data extraction, fraud detection, reserve setting, subrogation, and adjudication decision engines. Collaborate with underwriting, fraud, legal, and IT to integrate models into operations and improve efficiency, accuracy, and compliance.

Lead modernization of month-end and year-end close processes using AI and automation. Prepare, review, and validate journal entries, accruals, and financial statements. Implement anomaly detection, automated reconciliations, variance analysis, and predictive insights. Collaborate with data teams to structure finance data for ML use cases and design audit-ready, scalable reporting workflows.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

Design and implement AI/NLP solutions to automate insurance policy administration (issuance, endorsements, renewals). Translate policy language into models and rule engines, integrate with PAS, ensure regulatory compliance, monitor model performance, and support underwriting, operations, and exception handling.

Lead AI-enabled financial planning and strategic analysis, build data-backed business cases, refine unit economics, deliver executive-level insights, integrate ML into FP&A, and track KPIs to drive profitability and strategic decisions.

Build and maintain operating and cash-flow models, apply AI/ML and data techniques to automate forecasts, run sensitivity and scenario analysis, translate strategy into financial outcomes, support fundraising/M&A/pricing, and create dashboards and reports for stakeholders.

Lead integration of AI-driven tools into tax provision, planning, and multi-jurisdictional compliance. Design ML/analytics solutions for sales and payroll tax, enhance regulatory filings, support audits, and collaborate with finance, legal, and technology teams. Monitor tax regulation changes, document AI tax models for transparency and governance, and continuously refine models for scalability, reliability, and compliance.

The AI Implementation Engineer delivers and stabilizes AI solutions in customer environments, ensuring integrations and workflows meet requirements while coaching customer teams during critical phases.

The Senior Product & Growth Data Scientist will analyze user behavior, run experiments, shape product strategy, and influence growth metrics to drive company success.

Act as the technical owner for a portfolio of strategic voice-AI and real-time engineering customers: drive architecture reviews, deepen product adoption, coordinate LiveKit teams, lead executive reviews and on-site launches, surface product feedback, and define TAM playbooks to ensure long-term customer success and expansion signal.

As a Senior Enterprise Systems Engineer, you will lead projects, improve systems, support SaaS tools, and advocate for automation to enhance employee productivity.

Provide expert, client-facing support for institutional clients using Valitana's Vantage platform. Analyze fixed income and structured finance metrics, assist with compliance and data uploads, build custom workflows and Excel solutions, and deliver white‑glove service to maximize platform value. Occasional travel (≈10%) for conferences and events.

Design and ship production agents and reusable skills on ClickStack. Own the agent stack (context engineering, tools, MCP servers), integrate with ClickHouse telemetry, build SDKs and observability, optimize latency/cost, run evals, and collaborate with open-source contributors and customers.