Top Python Jobs in London

Lead integration and realization of BESS control and SCADA requirements, develop control logic for TSO integration, support commissioning and field troubleshooting, create test procedures (FAT/SAT), contribute to product controls development, maintain controls documentation and change control, and travel across EMEA.

Drives adoption, optimization, and customer success for Splunk’s security platform. Provides technical guidance on Enterprise Security and UBA use cases, configuration, and resilience; resolves complex challenges; collaborates with sales, support, and product teams; develops scalable processes and enablement materials; identifies expansion opportunities; and mentors team members. Requires substantial information security experience, Splunk certifications, SIEM expertise, security certifications, and proficiency across Unix, Windows, Bash, and Python.

Owns the end-to-end testing strategy, automation framework, and quality assurance for data warehouses, ETL pipelines, data models, AI tools, BI solutions, and data lakehouse projects. Leads test planning, execution, defect management, data validation, performance testing, reporting, and stakeholder assurance. Manages and develops a team of test analysts while partnering with engineers, architects, project managers, and business stakeholders across insurance functions.

Lead technical sales activities including discovery, demonstrations, proof-of-concepts, and architecture discussions. Translate customer data challenges into technical solutions using Python, Airflow, and related tools. Advise customers on DataOps, orchestration, observability, and automation while collaborating with account executives, product teams, and other stakeholders. The role is based in London and requires regular travel to France.

Graduate machine learning engineers will work with quantitative researchers on advanced machine learning and scientific computing problems. Responsibilities include implementing published research, developing custom libraries for large-scale model training, optimizing machine learning operations, profiling architectures, identifying performance bottlenecks, and evaluating ML hardware and software. Candidates should have strong object-oriented programming and machine learning skills, with experience in Python, PyTorch, NumPy, optimization, HPC, profiling, or model inference.

Perform hands-on quality assurance testing for web applications throughout the software delivery lifecycle. Responsibilities include creating and maintaining automated test suites, integrating tests into CI/CD pipelines, defining test strategies, managing defects, assessing risks, and collaborating with developers during Agile ceremonies from backlog refinement through release.

Lead DevOps initiatives across multiple squads: design and maintain CI/CD pipelines, manage Azure infrastructure with Terraform, integrate code-quality tools, implement monitoring and automation, mentor engineers, and optimize cloud services for reliability, performance and cost.

Build and optimize low-latency market data infrastructure, APIs, pipelines, curve builders, pricing integrations, and real-time distribution services for commodities trading. Partner with traders, quantitative analysts, risk, and operations teams to deliver production software. Lead adoption of generative and agentic AI workflows, while driving TDD, CI/CD, containerization, observability, performance tuning, deployment, monitoring, and production support.

Leads end-to-end development and architecture of enterprise Generative AI and Agentic AI products. Partners with business and technology stakeholders, shapes product roadmaps, builds AI agents using Google ADK and MCP, writes production-quality Python or Java, and drives testing, CI/CD, security, compliance, mentoring, and technical strategy.

Software Engineering Intern supporting hands-on development of real-world software for AI-enabled autonomous systems. The role involves collaborating with experienced engineers, contributing to mission-critical projects, and potentially deploying technology in challenging environments. Candidates should be entering their final undergraduate year in a technical subject, have strong software engineering skills, and programming experience in a server-side language such as Python, C++, Java, or Rust. UK right-to-work and security vetting are required.

Provides technical leadership for large-scale machine learning systems powering personalized recommendations, search relevance, AI Stylist experiences, retrieval, and generative AI. Owns architecture, system design, production delivery, reliability, MLOps, and engineering standards across teams. Partners with scientists, engineers, product managers, and senior stakeholders; mentors senior engineers and drives technical strategy, scalable platforms, and responsible AI adoption.

Embed with strategic customers to design, build, and implement data-driven AI solutions that improve customer support automation and Fin adoption. Analyze workflows and business challenges, establish measurement best practices, prototype and scale AI tools, and collaborate with Sales, Success, Product, and Engineering. Feed deployment insights back into product strategy while translating complex technical analysis into measurable business outcomes.

Design, build, and maintain scalable ETL/ELT pipelines, data models, schemas, and integrations across APIs, databases, and streaming platforms. Monitor data quality, optimize data architecture, and provide reliable datasets for analysts and stakeholders. The role also contributes to engineering best practices, CI/CD, infrastructure, and knowledge sharing.

Build and own Civic Marketplace’s data engineering foundation, including ingestion pipelines, canonical data models, entity resolution, data quality, lineage, freshness, and self-service analytics. Integrate messy public-sector sources such as APIs, files, webpages, and PDFs. Develop retrieval and vector pipelines supporting reliable AI procurement agents, while diagnosing data issues, operating production pipelines, and collaborating across engineering, customer success, and growth.

Build and scale a predictive modeling platform supporting multiple problem types and tenants. Develop embedding-based, temporal survival, and gradient-boosted models for social-domain risk prediction. Create training datasets, evaluation pipelines, and production ML infrastructure, while researching and safely deploying emerging ML and LLM techniques. Implement containerized APIs and Kubernetes services, and incorporate responsible AI, ethical, and regulatory considerations throughout development.

Build and maintain scalable data pipelines and infrastructure using GCP, BigQuery, Cloud Storage, Snowflake, SQL, dbt, and Python. Develop reliable data models, enforce data quality and governance, monitor pipeline performance, optimize queries and costs, support APIs and Power BI integrations, and collaborate with analytics, product, and engineering teams to deliver data solutions.

Develop machine learning and analytics solutions to optimize media buying, audience targeting, campaign performance, forecasting, measurement, and budget allocation. Build segmentation, experimentation, causal inference, and marketing mix models using Python and SQL. Create reusable analytical tools, dashboards, and self-service products, while translating complex findings into clear commercial recommendations for clients and senior stakeholders.

Lead profitable growth for NatWest Boxed’s unsecured personal lending business. Identify and execute growth initiatives with clients and channel partners, analyze performance data, optimize channel economics, and balance volume, risk, margin, and conversion with Pricing, Credit Risk, and Product teams. Develop initiative roadmaps, quantify commercial opportunities, and provide product roadmap requirements. Requires extensive unsecured lending or embedded finance experience, strong analytical and financial modeling skills, and proficiency with Excel, Python, or SQL.

Twelve-month internship supporting insurance and reinsurance clients with catastrophe risk modeling software. Responsibilities include client support, software and model training, quantitative risk analysis, customized outputs, consulting project participation, and interpretation of catastrophe loss results. The role requires strong analytical, probability, communication, organizational, and problem-solving skills, with Microsoft Office required and programming knowledge beneficial.

Own product control activities across valuation, P&L, risk, and reporting for gas and power trading businesses. Analyze financial positions, explain P&L movements, assess risk, support new products and markets, and provide actionable recommendations to stakeholders. Build and test models while automating and improving processes using Excel, VBA, SQL, Python, Power BI, and related systems. This fixed-term role requires strong financial product knowledge, analytical judgment, and the ability to influence business outcomes.

Provide incident handling, malware analysis, forensic investigation, remediation, detection engineering, and security automation across Windows, macOS, and Linux environments. Configure and optimize CrowdStrike Falcon modules, develop security content and automations, advise customers during incidents, produce technical findings, and support platform onboarding. The role also involves customer communication, thought leadership, operational improvement, and mentoring.

Supports live systematic trading operations by monitoring trading systems, orders, positions, P&L, risk, and exchange connectivity. Investigates production exceptions, coordinates issue resolution with traders and counterparties, supports deployments and releases, and improves monitoring, reconciliation, reporting, and operational processes through Python-based tools and automation. Includes local trading coverage and rotating weekend support.

Build and operate inference services and APIs for production world models. Responsibilities include deploying research models, optimizing GPU utilization, memory, batching, cold starts, reliability, and cost at scale. Collaborate with research and product teams to deliver new AI capabilities and customer-specific configurations. Requires strong Python, production API ownership, containerized GPU services, and hands-on inference performance optimization.

Engineer eukaryotic genomes end-to-end for mammalian cell systems: design and build editing reagents, perform mammalian cell culture and deliveries (transfection/electroporation/LNP/viral), isolate clones, verify edits via NGS and Sanger, and validate genotype-to-phenotype using molecular and cellular assays while optimizing efficiency and minimizing off-target effects.

Advise technology companies on building products with Claude. Responsibilities include hands-on customer engineering, pair programming, architecture reviews, code contributions, LLM application prototyping, evaluation framework development, technical documentation, developer content, workshops, hackathons, and collaboration with Product and Engineering teams. Travel to customer sites is required for implementation support and relationship building.