Top Python Jobs in London

Develop, train, and fine-tune machine-learned interatomic potentials (MLIPs) for magnetic and structural materials. Design DFT dataset workflows, active learning loops, and extend MLIP architectures to capture spin-lattice interactions. Build reproducible model and dataset pipelines and collaborate with materials scientists to translate physical intuition into training objectives.

Build and maintain software and orchestration that turns a physical lab into an autonomous system: implement instrument drivers, coordinate robots and data pipelines, automate workflows, integrate new instruments, and ensure reliability, error handling, and reproducibility while collaborating with materials scientists and ML researchers.

Design and own data architecture and ingestion pipelines that convert wet-lab instrument outputs into versioned, reproducible datasets for ML and RL training. Build tooling for dataset inspection, lineage, and integration with model training workflows, and collaborate closely with ML researchers to support pretraining, midtraining, and RL experiments.

Implement and scale cutting-edge ML research into production-ready systems: build distributed training and inference on GPU clusters, optimize model performance, create evaluation and experiment-tracking tooling, architect multimodal scientific data pipelines, and collaborate with researchers and materials scientists to deploy models in closed-loop hardware environments.

Lead ML research for an AI-driven materials discovery platform: design and prototype architectures (GNNs, generative, foundation models), develop active learning/optimization strategies, address representation learning for sparse noisy experimental data, collaborate with materials scientists to encode physics into models, and drive proofs-of-concept to production with engineering partners.

Develop and implement advanced theoretical and computational methods beyond standard DFT to predict intrinsic magnetic properties. Apply GW/DMFT and Green's-function many-body techniques, derive analytic formalisms, implement numerically, integrate with DFT production workflows, and collaborate with ML teams to improve predictive models and training data.

Lead technical vision and target-state architecture for large-scale, mission-critical enterprise systems. Design resilient hybrid/multi-cloud (Azure/AWS) data and AI architectures, champion governance/security, drive ARB processes, mentor senior engineers, own AI/ML integration and MLOps, and deliver hands-on prototypes and PoCs to ensure scalable, compliant production solutions.

Build, operate, and automate highly available, scalable cloud-native services. Design DevOps tools, implement CI/CD/GitOps pipelines, provision infrastructure with Terraform, manage large-scale Docker/Kubernetes environments, and develop monitoring/automation for distributed systems.

Conduct original alpha research on global macro assets, building and testing predictive signals (trend timing and directional). Model dynamics across rates, FX, equities and commodities, evaluate signals statistically, contribute to portfolio construction and risk analysis, monitor live strategy performance, and collaborate with researchers and portfolio managers to implement and refine trading strategies.

Run middle-office operational processes including NAV estimation, valuations, reconciliations, and P&L review. Validate fund administrator NAVs, maintain capital and portfolio records, support reporting and analytics, and help automate and improve processes while developing technical and market knowledge.

Support growth of non-ferrous metals trading by building and owning fundamental supply/demand models (initial focus on Copper, expanding to Aluminium). Produce forecasts, price outlooks, and market intelligence; maintain proprietary databases; use Python, SQL and analytical/AI tools; present insights to traders and senior management; collaborate with Trading, Risk and Operations.

Build and scale AI-driven backend systems and infrastructure for retail intelligence: develop the AI chatbot, agents, tooling and MCP integrations, evolve data processing across AWS and bare metal, own features end-to-end, and mentor team members.

Contribute to marketing effectiveness and data science projects: clean and prepare data, build and apply MMM and predictive models, create visualizations and dashboards, support client meetings, and deliver actionable media optimization recommendations.

Build and maintain shared platform tools and infrastructure to help squads ship faster and more reliably. Work both embedded with domain teams and on central platform projects: CI/CD, feature flags, canary rollouts, AWS infrastructure, observability, automation, AI integrations, and production support using metrics, logs, and SLOs.

Platform Engineer embedding across frontend, backend, data and warehouse teams to build shared infrastructure, CI/CD, feature flags and observability. Integrate AI across the engineering lifecycle, maintain core AWS/GCP services, automate toil, coach squads on SLOs and ownership, and proactively scope and deliver high-impact platform work.

Lead product-focused analytics and experimentation to uncover growth opportunities, define KPIs, analyze user behavior and retention, quantify feature impact, and communicate data-driven recommendations to cross-functional stakeholders.

Design, build and maintain scalable, automated cloud data solutions and pipelines. Provide technical leadership to a small engineering squad, own complex backlog tasks, develop data frameworks and standards, and ensure code quality via reviews and pair programming using Databricks, Python, SQL and Spark.

Design and maintain reliable data solutions, lead a squad of engineers, develop scalable data pipelines, and ensure adherence to data standards.

The Test Engineer will design and implement automated tests for data pipelines and cloud platforms, focusing on ETL testing and data validation.

Lead and grow a test and DevOps engineering team for a regulated medical device software stack. Own CI/CD, Yocto-based embedded Linux builds, signed update mechanisms, cloud data pipelines, test automation, compliance-as-code to IEC 62304/ISO 14971, and coordinate cybersecurity and release processes while contributing hands-on to architecture and code.

As a Software Engineer, you will design and manage cloud infrastructure, enhance DevOps practices, and collaborate with teams to drive innovation in drug discovery.

Serve as the primary technical lead for 2D/image pipeline and editorial workflows. Support editorial/story teams with ingest/export/tracking, manage playlists and vendor cuts, integrate review tools, configure burnins/slates/HUDs and OCIO colour workflows, propose and implement new tools (including AI), and assist artists, editorial and production on technical questions to deliver world-class animation.

Lead and enhance character build workflows by maintaining pipeline tools, advising artists, implementing automation and quality checks, and driving cross-departmental technical solutions to deliver efficient, high-quality characters for animation and games.

Design, build and maintain large-scale ETL/ELT pipelines and data models using Azure Data Factory, Synapse and Databricks. Implement CI/CD, ensure SLA-driven data delivery and reliability, manage code promotion and change processes, collaborate with cross-functional teams, support SAP Data Services end-of-life, and produce technical documentation and data dictionaries.

Design, automate, and operate secure cloud-native infrastructure and CI/CD pipelines. Prototype solutions, build IaC, containerised platforms, collaborate on reviews, document practices, and improve delivery and security.