Top Python Jobs in London

Own the technical strategy and customer journey for a portfolio of education institutions adopting OpenAI solutions. Lead discovery, architecture design, technical evaluations, prototypes, adoption roadmaps, governance, deployment readiness, and value realization. Build relationships with executive, academic, research, and technical stakeholders while coordinating specialist teams. Translate education needs into responsible AI use cases and reusable architectures, track adoption and customer impact, and provide feedback to Product, Engineering, and Research.

The Senior Algorithm Engineer will develop machine learning-enabled products for underwriting, manage algorithm integrity, and enhance digital processes while mentoring junior team members.

Supports digital forensics and incident response engagements by collecting and preserving digital evidence, conducting forensic analysis, investigating data breaches and security incidents, and preparing defensible client deliverables. The role involves working with multiple operating systems, cloud platforms, forensic tools, scripting languages, and security frameworks. Responsibilities also include supporting investigation teams, maintaining evidential standards, communicating with clients, potentially providing expert testimony, and traveling internationally up to 25% of the time.

Provides digital forensics, incident response, cybersecurity, eDiscovery, and investigative consulting for corporate, legal, and government clients. Leads forensic collections and analyses, supports investigations, produces defensible expert reports and testimony, and advises clients on cyber incidents. Requires expertise across operating systems, cloud platforms, networks, forensic tools, mobile devices, scripting, and log analysis. The role also involves client communications, business development, marketing support, and international travel of up to 25%.

Leads digital forensics and cyber incident response engagements, including evidence collection, forensic analysis, incident management, client deliverables, crisis support, and team leadership. Provides technical consulting across regions, maintains defensible evidential standards, develops proposals and project plans, supports business development, and serves as a subject matter expert. The role includes on-call availability, crisis deployment, client management, coaching professionals, and international travel of up to 25%.

Lead backend work for GitLab's Spec-Driven Development: design and build APIs, data models, evaluation systems, and agent-driven workflows using Ruby on Rails and Python. Ship production services, benchmark LLM workflows, coordinate multi-person projects, mentor engineers, and collaborate with product and design in an all-remote, async environment.

Develop and optimize machine learning and generative AI solutions for digital agents, including LLMs, NLP, RAG, retrieval, experimentation, evaluation, and statistical analysis. Build scalable data and ML pipelines using Python, SQL, and Spark; assess model quality, reliability, safety, and business impact; and support production deployment. Collaborate with engineering, product, and data science teams while mentoring less experienced colleagues.

Own the technical design, delivery, evaluation, and reliability of multi-component AI systems. Build data pipelines, evaluation frameworks, model-tool boundaries, feedback loops, and internal development harnesses. Ship LLM-backed products, optimize latency and cost, assess external models and datasets, and support APIs, SDKs, and agent-oriented applications. Participate in on-call rotation, conduct code and design reviews, and mentor engineers on evaluation practices.

Designs and implements cloud, bare-metal, and Kubernetes-based AI infrastructure across networking, compute, GPU, and storage. Develops scalable automation and production services, models database schemas, creates technical documentation, defines integration tests, and delivers infrastructure components into production. Requires strong experience with cloud-native architecture, Infrastructure as Code, GitOps, software development, and version control.

Supports Indonesian and broader Asian survey operations by monitoring data quality, managing quality-control staff, correcting survey issues, analyzing collection progress, and developing data-quality tools. Coordinates field operations, training, stakeholder engagement, translations, and backcheck processes. Provides insights on coffee and cacao sustainability data to country teams and supply-chain stakeholders. The role is fully remote from Indonesia with travel to regional agricultural areas.

Conduct qualitative and quantitative UX research for complex products and real-world environments. Frame research questions, select appropriate methods, conduct interviews, contextual inquiry, observation, field research, usability studies, surveys, and structured analyses. Systematically evaluate evidence, identify patterns, communicate findings clearly, and translate research into product and design recommendations. Collaborate with multidisciplinary teams, contribute to research practices, and develop mixed-methods expertise.

Leads design and execution of liquid-cooling R&D tests, including test-rig design, commissioning, instrumentation, data acquisition, analysis, and validation. Performs prototype assembly, leak and pressure testing, calibration, documentation, and configuration management. Presents technical findings, supports engineering change processes, maintains laboratory and safety standards, and drives continuous improvement for high-density cooling products used in data centers and critical infrastructure.

Build and deploy LLM-based and agentic AI solutions for customers using the Kinaxis Maestro Platform. Own customer engagements end to end, including prototyping, software and data engineering, production debugging, integrations, adoption, and mentoring. Collaborate with Product and Engineering to turn customer learnings into scalable platform capabilities while managing multiple priorities independently. Travel may be required up to 50%.

Build predictive customer lifetime value models, consolidate customer data, score leads, and send insights to Meta and Google advertising platforms. Own tracking, attribution, conversion infrastructure, offline uploads, and server-side setups. Translate behavioral data into marketing performance improvements while collaborating with performance marketing and go-to-market teams.

Support the development, testing, evaluation, and productionization of AI/ML models and applications, including LLMs, agentic systems, document AI, forecasting, and optimization. Collaborate with engineering, product, business, and client stakeholders to translate requirements into technical work, establish performance metrics, maintain governance documentation, and monitor production systems for accuracy, cost, latency, and business impact.

Build, maintain, and improve CI/CD pipelines and build infrastructure across development, testing, and release workflows. Optimize build performance, reliability, scalability, caching, dependency management, and reproducibility. Develop automation and developer tooling, operate CI infrastructure, troubleshoot pipeline failures, and improve CI/CD security and engineering workflows. Partner closely with software engineering teams to enhance developer experience and software delivery.

Price complex property, construction, specialty, and casualty insurance accounts; develop, test, calibrate, and maintain pricing tools and models; analyze portfolios and market trends; build dashboards and management reporting; support regulatory submissions; review pricing adequacy; consult on underwriting projects; and train underwriters on new platforms and tools.

Design, build, and deploy AI-powered products using frontier LLMs. Create agents, RAG systems, and backend services; evaluate and improve model quality, ensure trust/privacy, and collaborate with product, design, and finance teams.

Provide technical leadership for subsea pipeline, riser and tie-in spool design across project phases (pre-FEED to decommissioning). Perform mechanical analyses, check calculations, prepare and review deliverables, contribute to bids, represent the business in meetings, and support technology development and global coordination.

Own AI safety datasets from collection through labeling, quality control, versioning, and training readiness. Translate safety policies into consistent labeling and evaluation criteria, manage external contributors, and build production model evaluation workflows. Develop lightweight Python and SQL pipelines for reproducible data analysis, partnering with safety researchers, policy specialists, and ML engineers. The role also contributes to scalable dataset methodologies, quality standards, and human-in-the-loop processes.

Own the BAU IFRS9 process, produce and validate monthly outputs, develop and test model changes, maintain documentation and change logs, investigate model performance and movements, and support credit analysis and stakeholder queries. The role requires production-quality SAS and Python coding, credit risk reporting, impairment or capital modeling knowledge, and the ability to communicate analytical results to technical and non-technical audiences.

Analyze user, product, and business data to identify improvement opportunities and guide strategic decisions. Design and evaluate A/B tests, build dashboards and reports, communicate insights to cross-functional stakeholders, and use AI and automation to improve analytical workflows. The role partners with product, engineering, and marketing teams in a consumer digital product environment.

Graduate Analysts rotate through analytics placements covering technical skills, AI applications, data science, and product economics. They investigate business problems, analyze data, test ideas, build predictive models and self-serve tools, and communicate insights to stakeholders. Analysts may join credit strategy, product analytics, data science, technology, or risk teams, taking ownership of recommendations that improve products, customer experience, lending decisions, and business performance.

Build and maintain integrations with third-party billing and usage APIs, including authentication, synchronization, rate limits, error handling, schema changes, and self-service workflows. Develop the integrations framework, testing tools, customer-facing health and configuration interfaces, and API-first capabilities. Own features end to end across frontend, backend, databases, and cloud services while using AI tools throughout development.

Own and expand third-party billing and usage integrations for a cloud cost platform. Build and maintain ingestion pipelines, normalize vendor data, manage orchestration and backfills, and ensure financial-grade correctness through reconciliation, deduplication, and data quality checks. Use AI throughout the engineering workflow, collaborate with product and support teams, and improve integration scalability. The role requires strong SQL and Python, cloud data warehouse experience, REST API integration expertise, and production pipeline ownership.