Top Python Jobs in London

The Data Science Manager will collaborate with business partners, oversee predictive model building, manage a team, and deliver analytical insights to drive business decisions.

Responsible for tuning GPU cluster performance, troubleshooting InfiniBand networks, integrating hardware, enhancing automation, and managing GPU devices in HPC.

The Senior Site Reliability Engineer will ensure fault-tolerance and uninterrupted operations, using innovative cloud technologies, alongside improving CI/CD processes.

The Research Engineer will research, test, and deploy trading strategies, build research infrastructure, and collaborate on trading ideas while implementing solutions in Python and C++.

Hands-on engineering role to improve robustness, stability and performance of technology systems, with initial focus on redesigning and enhancing data pipelines. Perform technical analysis, implement changes, participate in coding and code reviews, and collaborate with production, engineering and business teams. Exposure to trading systems and data lake used for regulatory reporting.

As a Senior Data Scientist, you will optimize marketing performance, develop machine learning models, analyze A/B tests, and collaborate closely with marketing and data engineering teams.

The Senior Data Scientist will optimize marketing campaigns using data solutions, machine learning models, and collaboration with performance marketing teams to enhance business strategies at Preply.

The Quantitative Researcher will research market anomalies, perform data processing, optimize strategies, and maintain portfolio trading systems.

Design, customize and maintain analytics platforms; manipulate and visualize data; build statistical models and A/B tests; code in SQL and Python; generate insights, dashboards and presentations; collaborate with stakeholders and regional leadership to support campaign measurement and automation.

As a Research Engineer in Reinforcement Learning, you will develop and optimize RL infrastructure, push boundaries in AI research, and collaborate on scalable systems for large language models.

This role involves designing, testing, and deploying hardware as part of an Ultra Low Latency team. You’ll own the physical design flow while also understanding RTL and contributing across the chip design process.

The AI Research Engineer will develop AI models to enhance product autonomy, analyze extensive data, and deliver impactful solutions, driving innovative product features.

Develop and maintain firmware for high-volume home energy products across the full product lifecycle. Responsibilities include designing wireless communication solutions, implementing RF protocols, mobile interfaces, diagnostics and updates, shaping system architecture, conducting code reviews, and collaborating cross-functionally to deliver reliable products. The role requires hands-on embedded development using C and Python, IP networking protocols, Bluetooth/BLE, WiFi, Espressif hardware, and laboratory test equipment.

Build and operate shared AI platform infrastructure for LLM applications, agents, RAG, tool calling, and AI workflows. Develop data and knowledge pipelines, secure enterprise integrations, reusable frameworks, deployment and observability standards, and developer tooling. Take AI systems from experimentation to reliable production while ensuring security, privacy, governance, scalability, quality, and cost efficiency. Collaborate across Engineering, Product, and IT to establish practical AI platform patterns and guardrails.

Own technical architecture for enterprise and regulated-industry Plane deployments from discovery through implementation. Design self-hosted and air-gapped environments, address security and compliance requirements, define migration strategies, support major sales engagements, and translate customer requirements into scoped engineering requests. The role requires strong knowledge of on-premises infrastructure, networking, identity federation, security questionnaires, technical documentation, and customer-facing technical communication.

Hands-on senior cloud infrastructure engineer to design, build, and run a multi-tenant AWS SaaS hosting platform. Responsibilities include Terraform and Puppet infrastructure, Python automation, etcd-based service discovery, multi-tier caching, observability (Prometheus/Grafana/Loki), incident response, and platform reliability improvements.

Lead the design, development, and verification of high-performance autonomy solutions for the defense industry, involving algorithms, system architecture, and mentoring.

Senior IT Systems Engineer supporting Stockholm and Geneva data centers. Design, migrate and operate hybrid/public cloud and on-prem infrastructure (Windows, Linux, VMware, Kubernetes), manage storage and networking, analyse outages, deliver documentation, perform on-call/emergency tasks, and collaborate with developers, product owners and support teams to ensure secure, high-quality services.

The Senior Enterprise Architect leads the design and implementation of network and cloud architectures, ensuring alignment with organizational goals and industry practices. Responsibilities include defining architecture frameworks, advising on cloud adoption, ensuring security compliance, and managing cross-functional teams.

Lead growth-focused data science initiatives, owning LTV prediction models across countries and channels. Translate business questions into models, analyze large customer and marketing datasets, evaluate acquisition quality, monitor and productionise models with engineering partners, and drive data-informed growth and retention decisions.

Design, tune, and maintain production prompts and guardrails for LLM-driven agents. Build evaluation suites, run A/B tests, implement feedback loops, optimize cost and model selection, ensure multi-language B2B tone, and document patterns and test results.

Design, build, and operate core backend systems powering the Curie platform (APIs, data pipelines, graph databases, integrations with AI models). Own feature lifecycle from design through deployment and monitoring, improve observability and reliability, write well-tested maintainable code, collaborate with ML researchers and domain experts, and mentor peers.

Lead a pricing team for Casualty, Financial and Professional Liability products across company and Lloyd's platforms. Develop and deploy pricing models, provide case pricing for complex accounts, support underwriting strategy, portfolio monitoring, reinsurance decisions and capital modelling. Drive pricing transformation, governance and automation while mentoring a small team and collaborating with underwriting, finance, BI/IT and compliance.

Define and implement evaluation frameworks and automated test pipelines for agentic AI (MCP tools and Skills). Test tool invocation, multi-step workflows, and mitigate failure modes (hallucination, misuse, latency). Produce evidence for PTB/PTO, partner with ML engineers to embed testability, and shape long-term quality and governance for federated MCP contributions.

Design, build, and operate agentic AI platform components (MCP servers, Skills, QAS). Implement agent orchestration, tool‑calling, secure API wrappers, and RAG-based integrations. Collaborate with product teams, QA, and SRE to ensure governed, production-ready deployment and developer experience for enterprise AI agents.