Top Python Jobs in London

Leads measurement strategy across PlayStation by designing experiments, causal inference methodologies, statistical models, and machine learning solutions. Establishes experimentation best practices, influences platform capabilities, partners with product and business leaders, communicates analytical recommendations, and mentors data scientists and analysts. The role provides technical leadership for evidence-based product and commercial decisions affecting millions of players.

Leads large-scale data curation, enrichment, and rare-event mining for autonomous vehicle machine learning systems. Builds workflows for model introspection, out-of-distribution detection, robust evaluation, and driverless operation. The role spans model engineering, infrastructure, compute, and data, requiring ownership of distributed ML systems, large-scale inference, and collaboration across research and engineering teams.

Build and maintain reliable infrastructure management tooling for cloud-based banking software. Responsibilities include automating deployments, developing observability and orchestration tools, supporting scalable and highly available services, contributing to disaster recovery and backup strategies, and improving code quality and engineering processes. The role uses Python or Golang and involves cloud platforms, databases, event streaming, container orchestration, and CI/CD systems.

Develop reliable, mission-critical software and AI capabilities for semi-autonomous platforms operating in complex, changing environments. Engineers solve challenging problems with code, contribute to systems design, collaborate through code reviews and pair programming, and communicate architectural decisions clearly. The role involves technical interviews covering systems design, project deep dives, and live coding. Work may span distributed systems, AI, deployment infrastructure, robotics, and edge applications, with strong emphasis on ethical engineering, independent reasoning, reliability, and safety.

Early-career software engineer developing reliable, mission-critical software and AI-enabled capabilities for semi-autonomous platforms. The role involves solving complex engineering problems, reasoning about system architecture, writing code independently, collaborating through code reviews and pair programming, and communicating technical decisions clearly. Candidates are assessed through a project walkthrough, systems design discussion, live coding, and leadership interview. Experience with Python, Rust, backend interfaces, cloud-native or edge architectures, hardware interfaces, or robotics is beneficial.

Embed with enterprise customers to identify operational problems and rapidly design, build, deploy, and improve AI-powered software. Develop full-stack features, APIs, event-driven services, integrations, data pipelines, retrieval systems, model-serving workflows, and agentic applications. Lead technical discovery, productionize prototypes, monitor real-world usage, improve reliability, and communicate trade-offs to technical and non-technical stakeholders. Feed customer insights into product roadmaps.

Own end-to-end delivery of AI workflows across the full stack, translating ambiguous healthcare requirements into high-quality products. Collaborate directly with customers and product teams, gather field insights, improve the core product, and contribute to engineering quality, velocity, and team culture. The role requires working from the office or customer sites five days per week.

Paid 10-week actuarial internship involving large-data analysis, actuarial modeling, risk pricing, client presentations, reports, meetings, and insurance business development projects. Candidates will learn insurance and reinsurance while working with experienced actuarial specialists. The program is intended for penultimate-year students in numerate disciplines and may lead to a deferred 2028 graduate offer.

Develop and maintain scalable Python software for a systematic multi-strategy trading platform. Collaborate with quantitative researchers on strategy and portfolio development, ensure production code is robust and performant, improve platform capabilities, and support live production systems through a rota. The role spans the full trading technology lifecycle, including data, research, execution, monitoring, and platform reliability.

Manage and architect cloud and self-hosted infrastructure for a regulated bank. Responsibilities include operating FoundationDB and Kubernetes, building infrastructure as code, maintaining Bazel and CI/CD systems, improving reliability through multi-region failover and chaos engineering, managing security access and observability, optimizing cloud costs, and supporting hybrid-cloud infrastructure. The role requires strong systems, networking, cloud, programming, and production reliability experience in a high-autonomy startup environment.

Design, build, and optimize scalable software platforms supporting quantitative research and financial trading. Responsibilities include developing trading systems, modeling and simulation frameworks, research tools, machine-learning infrastructure, and high-performance distributed systems. The role involves collaborating with quantitative researchers, owning solutions end to end, applying strong software fundamentals, improving scalability and performance, and evaluating emerging technologies.

Build and deploy production AI systems embedded within product teams. Translate business workflows into AI solutions, integrate existing services, scope and develop new capabilities, and work across data pipelines, model training, serving, MLOps, APIs, and cloud infrastructure. Ship rapid prototypes and productionize them with monitoring, evaluation, feedback loops, and reliability. Collaborate with product owners, stakeholders, and engineering teams to shape the AI services roadmap.

Build and maintain scalable data platform solutions supporting analytics and business decision-making. Collaborate with product, analytics, and engineering teams to solve complex problems, improve data reliability, manage infrastructure, and enable fast insights. Responsibilities include developing data-intensive systems, working with cloud platforms and warehouses, applying infrastructure-as-code and CI/CD practices, and balancing scalability, cost, security, and delivery speed.

Architects and deploys multimodal 2D/3D object detection and tracking models using camera, LiDAR, and radar data. Owns perception data collection, dataset development, evaluation pipelines, production monitoring, and the perception system roadmap. The role also requires cross-functional leadership and mentoring junior engineers.

Build and operate high-throughput trading data pipelines, analytics engines, time-series models, and analytical databases. Develop internal AI platforms, RAG pipelines, prompt-management tools, and controllable agent systems. Optimize systems for reliability, performance, data quality, reconciliation, monitoring, and cost. Collaborate with quantitative trading teams using financial and cryptocurrency datasets, market data, and trading metrics such as PnL, risk, balances, and trade activity.

Own global sales compensation operations, including commission modeling, forecasting, payroll validation, exception approvals, dispute resolution, clawbacks, reconciliations, risk management, and SOX controls. Partner with Sales, Finance, Payroll, Legal, HR, and Compliance leaders to ensure accurate, timely, transparent, and audit-ready commission payments. Lead plan effectiveness analysis, stress testing, governance, and process improvements while explaining complex payout calculations to stakeholders.

Conduct frontier applied research on efficient AI model architectures, including sparse attention, long-context memory, selective computation, dynamic inference, reasoning, and continual adaptation. Formulate research questions, design rigorous experiments at meaningful scales, develop efficient implementations, publish findings, contribute to open-source tools and models, mentor researchers, and help direct the research stream.

As a Deployment Strategist, you will engage with customers to address their data-related challenges, develop workflows, integrate data streams, and support user training, presenting findings to diverse audiences.

The Senior Backend Software Engineer will design, develop, and maintain scalable backend services, optimize applications, build APIs, and collaborate across teams to improve user workflows and product efficiency.

As a Deployment Strategist, you will address complex operational challenges by analyzing data, collaborating with clients, and developing tailored solutions to enhance decision-making processes.

Work onsite with NATO customers to design and implement data-driven software solutions. Own end-to-end projects: architect systems, wrangle large-scale data, build web apps, collaborate with technical and non-technical stakeholders, and iterate rapidly in high-stakes environments.

The Forward Deployed Enablement Engineer supports customer success by resolving technical issues, enhancing tools, and ensuring efficient workflows on Palantir's platforms.

Backend Software Engineers at Palantir build scalable software solutions, collaborate across teams, and develop systems for data processing and storage, enhancing product capabilities.

Backend Software Engineers at Palantir build and maintain scalable backend services, develop APIs, optimize applications for performance, and collaborate across teams to shape user workflows.

The Forward Deployed Software Engineer at Palantir collaborates with customers to architect and build AI-driven solutions using large-scale data to address critical challenges.