Top Python Jobs in London

Design, build, test, and operate scalable identity and authorization services for a global fintech platform. Lead architecture and code reviews, participate across the SDLC, maintain CI/CD best practices, and collaborate with cross-functional teams to deliver secure IAM and FGAC solutions.

Lead design and delivery of production LLM-powered agent systems and firm-wide agent standards. Build reference agent apps, connect agents to internal data/APIs, establish security and governance for AI, adopt deployment and observability infrastructure, and partner with stakeholders to identify high-value use cases.

Lead technical direction across platform squads, ship and operate critical platform services, improve CI/CD and delivery workflows, drive reliability (SLOs, observability, runbooks), remediate production issues, mentor engineers, and participate in on-call and incident response to raise platform quality and developer experience.

The Human Data Operations Strategist manages data annotation projects, optimizes workflows, ensures high data quality, and collaborates with clients and teams for AI model development.

Design, build and deploy machine learning and AI solutions end-to-end: data exploration, feature engineering, model selection, evaluation, deployment, maintenance, and tooling to scale ML across products.

Build and lead the Data Labeling team, define annotation guidelines and QA frameworks, partner with researchers to create labeling workflows, prioritize projects, monitor metrics, improve tooling and automation, manage vendors, run complex AI evaluation projects (RLHF, safety, benchmarks), and communicate insights to leadership.

Lead technical development and production deployment of ML models for search, personalization, ranking, and recommendations. Build scalable, explainable ML solutions, own end-to-end impact, collaborate with backend and product teams, and iterate on experiments using cloud-native data at scale.

Lead technical ML efforts to detect and prevent financial crime by designing, developing and shipping production deep learning, graph and sequence models. Provide IC technical leadership, mentor peers, work with product, engineering and MLOps to iterate models on a cloud-native platform, and measure production impact while minimising false positives and operational costs.

Design and build a centralized observability platform for satellite and deep-space networks. Implement metrics, logging, and tracing (Prometheus, Loki, Tempo/OpenTelemetry), define SLOs/SLIs/error budgets, automate deployments with IaC and GitOps, integrate observability into Kubernetes and cloud environments, support engineers with instrumentation and tooling, lead monitoring/alerting/incident response, and participate in on-call rotations.

Serve as the technical bridge between physical-layer communications and software orchestration: build and maintain Spacetime system models, write production adapter layers (Python/Go), design data schemas (Protobuf/JSON/gRPC), perform link-budget and propagation analyses, lead tier‑3 triage for live networks, and collaborate with product and engineering to convert integrations into reusable features.

Lead architecture and delivery of enterprise-scale data and AI projects on Google Cloud. Provide pre- and post-sales technical advice, design and migrate cloud solutions, mentor architects, collaborate with partners and sales, define best practices, and build next-generation ML products and scalable production-grade platforms.

Design, build and maintain production-grade Python services and scalable APIs supporting risk analytics. Collaborate with Risk Managers and Quants to productionise models, ensure performance, reliability, observability, and improve engineering standards using cloud-native practices and AI-assisted tools.

Design, build and maintain modular, scalable, performant backend systems across the full software lifecycle; diagnose and resolve system issues; mentor junior engineers; collaborate with product and cross-functional teams; iterate quickly to deliver customer-focused features.

Lead design, build and deployment of production AI workflows embedded with business teams using Microsoft Copilot Studio, Azure AI Foundry and Microsoft Fabric. Own API integrations, CI/CD, MLOps/AIOps, testing, documentation and handover. Provide senior technical leadership, set standards, rapidly prototype in sandbox environments and ensure reliable, secure, production-ready AI solutions connected to enterprise systems (SAP, Salesforce, data lake).

Work with sales teams and partners to demo Snowflake's AI Data Cloud, run proofs of concept, design solutions, and close enterprise deals. Engage executives and technical audiences, position Snowflake against competitors, and collaborate with product, engineering, and marketing to improve offerings.

Contract Databricks Engineer to design and deliver cloud data lakehouse solutions (AWS/Azure), lead and mentor data engineers, run hands-on development (SQL/Python/PySpark), drive migrations and medallion architecture implementations, engage clients, shape technical strategy and support delivery and pre-sales.

Analyse portfolio performance and credit risk; own analytical projects end-to-end; build forecasting models and monitoring dashboards; present insights to stakeholders; partner cross-functionally to optimise risk strategy, pricing and operations.

Build and maintain high-performance, data-driven web applications for market data and trading services. Design full-stack solutions, implement features, write tests, support production, participate in planning and reviews, mentor engineers, and produce documentation and specifications.

Design, build, test, and deploy smart contracts and decentralized applications. Maintain blockchain integrations and backend services, optimize for security and gas efficiency, contribute to architecture and technical strategy, conduct code reviews, mentor junior engineers, and collaborate with product, frontend, and security teams.

Analyze large financial datasets, validate and develop automated models, model corporate actions and index changes, write client-facing research reports, communicate insights to clients, and source public information.

Act as a subject-matter expert for Agentforce/Data Cloud, engage strategic customers to optimise architecture and performance, identify capability gaps, run tailored playbooks, influence executives on tech-to-business value, build partner relationships, and mentor peers to drive customer success and adoption.

Design, develop and optimize trading systems and market-making algorithms; analyze complex datasets to inform stakeholders; build scalable, reliable client-facing products; implement controls and monitoring; serve as L3 SME during market stress and production incidents.

Build and own backend platform systems around AI models: design APIs, data models and schemas, implement integrations and data pipelines, create internal libraries/tooling, and drive features end-to-end from design to production while collaborating with engineers and AI specialists.

Bridge patent practice and AI product development: engineer LLM outputs for patent tasks, build legal benchmarks and datasets, drive product roadmap, run pilots with global IP teams, and document AI adoption playbooks.

Lead development and production deployment of proprietary LLM-based algorithms and high-scale evaluation pipelines. Implement advanced prompt engineering, ship evaluation frameworks, and work across the stack (Python, Postgres, TypeScript/React) to translate research into production-ready AI products.