Top Python Jobs in London

Lead development and productionization of large-scale ML and GenAI products. Own end-to-end data science lifecycle: prototyping, model development, benchmarking, deployment, monitoring, and stakeholder communication. Collaborate with domain experts to define metrics, optimize models (including LLM fine-tuning and embedding retrieval), and build scalable pipelines and integrations (OCR, table extraction, multimodal and GNN solutions).

Design, build, and operate scalable production data pipelines and storage. Model analytics and semantic layers, ensure data quality and observability, enable self-service, mentor engineers, and collaborate across engineering, product, and design.

Design and implement end-to-end data solutions using Microsoft Fabric, Azure, Databricks and Spark; build ETL/ELT pipelines, data models and Power BI dashboards; ensure data governance, quality, performance tuning, and translate business needs into technical specifications while supporting public-sector clients and undergoing required security clearance.

Hands-on senior SRE owning parts of a reliability platform across a hybrid AWS/Nomad estate. Implement observability with OpenTelemetry, define SLOs/error budgets, build CI/CD and safe release patterns, design self-healing and chaos experiments, run incident response and PIRs, mentor engineers, and author SRE standards to embed reliability across teams.

Lead and grow a DevOps/Platform team while hands-on engineering Kubernetes-based, multi-cluster, multi-region platforms. Drive GitOps, IaC, progressive delivery, zero-trust security, observability, SLO/resilience practices, and compliance automation. Collaborate with Security, Data, and AI teams to deliver AI gateway infrastructure, disaster recovery, and platform reliability across cloud environments.

Triage and resolve platform-related tickets and non-critical alerts, investigate issues end-to-end, escalate complex problems, maintain and improve runbooks and documentation, and contribute to tooling and automation to reduce toil while communicating with technical and non-technical stakeholders.

Design, build, and maintain performant PostgreSQL datastores, scalable data pipelines, and production-ready Python HTTP APIs. Ensure data quality, integrity, and query performance for financial datasets. Collaborate with researchers and clients to translate needs into features, using automated testing to own features from conception through deployment.

Lead design and deployment of Generative AI/LLM solutions: prompt engineering, fine-tuning, embeddings, RAG pipelines, vector DBs, and end-to-end APIs. Collaborate with engineering and product teams, evaluate model performance, mitigate bias, and optimize production workloads.

Supervise first-line trading activity on the Ring and LMEselect, determine and publish reference and closing prices, enforce dealing regulations, manage error trade policy and dynamic price bands, provide market surveillance and stakeholder support, and contribute to pricing-related projects, documentation and training.

Join an agile digital marketing team to develop, test, deploy and support WordPress, WooCommerce and React-based websites and eCommerce features. Participate in planning, demos, QA, deployments, continuous improvement and performance/stability work across the platform.

Pre-sales solution engineer driving AI Data Cloud adoption: lead technical demos, design and support proofs-of-concept, articulate value to executives and technical teams, and close enterprise deals while collaborating with product and engineering.

Work with account teams and partners to solve complex data problems, demonstrate Snowflake via demos and proofs-of-concept, design solutions, build technical champions, and represent Snowflake at events while collaborating with Product, Engineering, and partners to drive customer success and close deals.

Build and maintain production-grade data pipelines, design data models and infrastructure, enable API access, govern data assets, and collaborate with actuaries, data scientists, and engineers to support algorithmic underwriting and MLOps.

Lead and grow a data engineering squad to design, operate, and secure a scalable self-service data platform. Define roadmap, enforce architecture and SRE best practices (CI/CD, IaC, SLOs), collaborate with product, analytics, security and vendors, and drive platform delivery and integrations.

Provide 1st-3rd line application support across multiple systems: investigate and resolve incidents, monitor performance, support releases, perform root cause analysis, maintain documentation, and act as technical lead on projects, including on-call duties.

Lead end-to-end analytics workstreams for market and brand engagements: market sizing, commercial and financial modelling, data aggregation, hypothesis-driven analysis, quality assurance, client presentations, and mentoring junior analysts to deliver actionable strategic recommendations.

Design and own production GenAI infrastructure for open-weight LLMs and VLMs: real-time GPU serving, high-throughput batch inference, and fine-tuning. Architect autoscaling GPU pipelines, observability, cost controls, and platform surfaces (LLM/Agent Gateways, evals, guardrails). Lead technical direction, mentor engineers, and partner with ML and product teams to deliver reliable, low-cost, high-performance GenAI services to production.

Support development and maintenance of in-house fund management tools, automate processes, analyse and attribute portfolio performance, support data pipelines, and resolve issues for internal stakeholders.

Middle-office role supporting trading desks: monitor trading activity, perform daily PnL reconciliation, investigate breaks, resolve trade issues, escalate pricing/risk problems, and drive data-driven process improvements and automation.

Design, build, and deploy end-to-end document understanding and search-led AI solutions for legal content: semantic chunking, document enrichment, knowledge graph construction, synthetic data generation, and model compression. Collaborate with engineering and product teams to scale production systems, define evaluation strategies, and advance research through publications and IP.

Set up and run flesh, hair, cloth and rigid-body simulations, develop and maintain animation rigs, debug rigs and simulation setups, and script tools/plugins. Collaborate with supervisors and team members, document workflows, and deliver VFX work for feature films.

Optimize transformer-based ML inference for edge accelerators and GPUs. Implement and validate compiler, runtime, and kernel optimizations; profile end-to-end inference stacks; build benchmarking and regression tests; target multiple platforms (NVIDIA, Qualcomm); collaborate with model developers and cross-functional teams to deliver performant, maintainable on-vehicle ML systems and contribute to technical roadmaps.

Build and maintain RegTech SaaS features by translating business requirements into technical specifications. Contribute to product roadmap, architecture, testing (TDD), and collaborate with PMs, BAs, and engineers to deliver reliable, secure, maintainable code for regulatory reporting solutions.

Build end-to-end prototypes (frontend, backend, APIs, data integrations) for industrial AI, Digital Twins, robotics and edge scenarios. Implement and test REST APIs, fix bugs, add basic tests, follow security best practices, document setups, and collaborate in multidisciplinary teams while using AI-assisted tools and container/cloud deployment.

Develop, implement, and maintain pricing and calibration models and curve construction frameworks for inflation derivatives (swaps, caps/floors, options). Collaborate with traders, structurers, risk and model validation to ensure robust, performant production analytics. Implement and test models in production libraries, monitor performance, produce documentation, and stay current with market practice and regulatory expectations.