Top Python Jobs in London

Lead design and implementation of ML/LLM systems for ingestion, knowledge extraction, retrieval, and reasoning. Build datasets, metrics, pipelines, agentic retrieval and RAG solutions. Establish MLOps, orchestration, observability, and experiment tracking. Collaborate on research agenda, shape ML architecture, and hire and grow the ML team.

Design, build, and lead development of AppGlass features; develop AI-first tooling and automation; implement enterprise integrations and deployments across Kubernetes and cloud; and improve reliability, testing, performance, and security for production use.

Develop and maintain SFT and RL post-training pipelines for multi-step coding agents, train and adapt LLMs for agent workflows, build evaluation and simulation environments, design metrics and evaluation frameworks, analyze results to improve models and datasets, and collaborate with research, product, and infra teams to ship models into JetBrains IDEs.

Design, train, and deploy large language models from scratch; convert business requirements into technical specs; collect and process pretraining/fine-tuning datasets; run distributed training on large GPU clusters; support and improve production ML subsystems and tooling.

Lead design and implementation of AI-native features for PyCharm and Python tooling. Architect integrations (MCP, agents), prototype and ship features, guide engineering decisions, evaluate AI tools/providers, and expose IntelliJ Platform capabilities to AI workflows while collaborating with product, ML, QA, and senior developers.

Lead analytics for clinical trials by converting complex clinical data into actionable insights, partnering with data quality and monitoring teams, using visualization tools, advancing anomaly detection and risk‑based analytics, and implementing interventions to improve data quality and study timelines.

Four-month, full-time research fellowship focused on ML systems and performance. Fellows build and evaluate infrastructure-heavy projects (e.g., CPU simulators, accelerator backends, large-scale distributed training), use external models/APIs, receive mentorship, funding for compute, and aim to produce public research outputs.

4-month full-time funded research fellowship using external models/APIs to produce public outputs (papers). Fellows receive mentorship, workspace access (Berkeley or London) or remote options within US/UK/Canada, weekly stipend, compute funding, and are expected to implement experiments, collaborate with mentors, and communicate results. Applicants must be fluent in Python and authorized to work in the US, UK, or Canada.

Four-month full-time research fellowship supporting empirical AI safety projects using external models and APIs. Fellows receive mentorship, compute funding, and workspace access to produce public outputs (e.g., papers) across safety, robustness, interpretability, RL, and societal-impact topics.

Four-month full-time research fellowship mentoring fellows to run empirical RL and LLM projects using external infrastructure. Fellows receive compute funding and a weekly stipend, produce public outputs (e.g., papers), and work on RL environments, algorithms, model fine-tuning, and training/evaluation of large models with mentor support.

Identify and prioritize automation opportunities across customer service and collections, build business cases, design and co-develop AI-driven solutions, lead cross-functional stakeholders, and present outcomes to senior leadership.

The role involves modernizing backend systems by developing and maintaining Python services using TDD, leveraging AI tools, and ensuring quality through rigorous testing and DevOps practices.

Lead sustainability data and analytics strategy for investment research, assess climate impacts on portfolios, build scalable data and AI-enabled workflows, manage client exclusions and Net Zero frameworks, and translate quantitative insights for stakeholders across asset classes.

Build and ship features for DeepEditor and TrueSync across the full stack. Collaborate with science, product, and creative teams to design scalable, reliable AI-powered editing and localization systems. Drive projects from concept to production, improve performance and quality, mentor engineers, and influence architecture and engineering practices.

Build and optimize ML infrastructure and data platforms for large-scale multimodal datasets, supporting training, evaluation, lifecycle management, and production inference. Work on data ingestion, distributed training, experiment tracking, model versioning, and scalable serving while improving reliability, performance, and observability. Provide technical leadership at senior levels.

Design, build, and maintain scalable data pipelines and storage for fraud detection. Support fraud analytics, feature engineering, model integration and serving, pipeline monitoring, and documentation. Collaborate with data, product, and engineering teams to enable detection, reporting, and operationalisation of fraud models.

Build, deploy, and maintain LLM-powered applications and coding-agent workflows for enterprise clients. Prototype with agent platforms, integrate to client systems securely (GDPR), implement monitoring, CI/CD, and token tracking, create reusable AI assets, and coach teams to production-grade solutions.

Lead adoption of electronic FX execution across corporate sales, engage and educate clients on eFX platforms, partner with trading, tech and quant teams to optimise pricing, execution and product roadmap, and support platform rollouts and execution analytics.

Design and build ML, NLP, and generative AI systems for scientific discovery and knowledge extraction. Work with large heterogeneous scientific datasets to develop semantic search, entity extraction, QA, summarization, embeddings, and production-ready models. Implement model evaluation, fine-tuning, deployment, monitoring, drift detection, and scalable data pipelines while collaborating across engineering, product, UX, and research teams.

Lead design and build of finance data models, Looker dashboards, and automated month-end and cash-management pipelines. Drive BI architecture, exploratory analysis, investor reporting, acquisition data integration, and deploy generative AI/automation for financial commentaries. Act as cross-functional translator and steward of sensitive financial data.

The role involves using SQL and Python to develop automated solutions for risk management, improve process monitoring, and collaborate with various teams to enhance data-driven decision-making in banking operations.

Build and scale an enterprise Generative AI platform. Own large product areas across backend and frontend, develop reliable Python backend services, integrate LLMs, vector databases, and AI infrastructure, work with distributed systems and data pipelines, and ship features quickly while collaborating with product, ML, and infrastructure teams.

Lead subscriber growth and health analytics for Disney+ EMEA: generate insights from data, design experiments, develop dashboards and visualisations, communicate clear recommendations to stakeholders, embed self-serve analytics, and collaborate across regional and international teams to inform acquisition, retention and product strategy.

Lead spatial and sustainability analysis for public-sector tenders: model resourcing scenarios, run GIS and SQL analyses, build Excel forecasting models, perform high-level carbon modelling, automate data workflows, liaise with operations, and present findings to clients and senior management to win contracts.

Lead actuarial pricing and portfolio management for Financial Lines and Cyber across regions. Build, calibrate, and review rating models; support underwriters on large accounts; run profitability studies and business planning; manage reinsurance submissions; improve data and analytics practices; produce management reporting and present to product boards. Line-manage actuarial analysts and collaborate with claims, reserving, reinsurance, and capital modelling teams.