Top Python Jobs in London

Own optimization of LLM and VLM inference systems from model artifacts through production deployment. Improve latency, throughput, memory efficiency, GPU utilization, quality, reliability, and cost per token. Deploy and extend inference engines, build compression and quantization workflows, implement decoding and KV-cache optimizations, create reproducible benchmark harnesses, diagnose production regressions, and collaborate with kernel, platform, research, infrastructure, product, and customer teams.

Lead Samsara’s vulnerability management and application security programs across cloud, firmware, IoT, and corporate systems. Define technical strategy, automate vulnerability detection and response, reduce remediation time, guide engineering teams, mentor security engineers, investigate critical vulnerabilities, and support incident response. The role requires strong AWS, programming, vulnerability management, application security testing, AI/LLM, and security automation expertise.

Own strategic customer engagements from discovery through delivery and adoption. Scope AI coding projects with executive sponsors, lead technical discovery and architecture reviews, configure workflows and integrations, partner with Forward Deployed Engineers on builds, train customer teams, monitor feasibility, identify expansion opportunities, and communicate product gaps to Engineering and Product. The role requires translating business outcomes into technical implementations while maintaining executive relationships and delivering measurable value quickly.

Owns technical strategy and customer outcomes for enterprise AI adoption across ChatGPT Enterprise, the OpenAI API, Codex, and agentic solutions. Leads executive discovery, AI architecture, technical evaluations, prototypes, production-readiness planning, adoption roadmaps, and measurable business impact. Partners with sales, engineering, deployment, security, product, research, and implementation teams while advising CTO, CIO, CISO, and engineering stakeholders.

Evaluate and onboard cross-asset market data feeds, maintain and enrich reference databases, improve data QA, liaise with vendors, produce analytics and reporting, support product development and client requests across TCA, venue analytics and trade surveillance.

Supports quarterly P&C reserve reviews across international insurance portfolios, including Solvency II technical provisions and Lloyd’s regulatory returns. Leads portfolio deep dives, reserve-risk analysis, process improvements, actuarial reporting, and stakeholder collaboration. Coordinates analysts, develops reserving methods and tools, supports internal model validation, and communicates findings to management, underwriters, claims teams, regulators, and auditors.

Own end-to-end scientific data pipelines from ingestion through trusted, model-ready datasets. Model compounds, structures, assays, predictions, and experimental results while ensuring data quality, lineage, governance, and observability. Partner with ML engineers, data scientists, and researchers to build scalable solutions, shape data architecture, develop self-service and API capabilities, and mentor junior engineers.

Analyze European alternative data to develop macroeconomic insights relevant to rates and FX markets. Produce written, verbal, visual, and data-feed research for investment professionals. Collaborate with data scientists, engineers, data sourcing teams, and Compliance to evaluate data assets, model time series, and deliver actionable investment research.

Conduct post-trade surveillance across LSEG markets to identify potential market abuse and financial crime. Analyze large trading datasets, investigate alerts, raise trading queries, present cases, submit STORs, optimize surveillance alerts, and improve data manipulation and visualization processes. Maintain procedures and alert documentation while collaborating with quantitative surveillance and technology teams. The role requires strong knowledge of secondary markets, UK and European market abuse regulations, analytical judgment, communication, and organizational skills.

Build and operate Encord’s cloud infrastructure, deployment pipelines, Kubernetes platforms, automation, observability, and reliability processes. Design scalable infrastructure across GCP and AWS, optimize performance and capacity for large data workloads, define SLIs/SLOs/SLAs, improve incident response, and collaborate with engineering squads to promote resilient, automated DevOps practices.

Conduct cutting-edge NLP and machine learning research, develop benchmarks and baselines using public datasets, train large language models on practical tasks, and publish findings at leading conferences and journals. The role requires advanced academic training, research publications, and hands-on experience with Python, PyTorch, Hugging Face, Transformers, and LLM techniques such as fine-tuning, self-learning, efficiency, agents, and reasoning.

Research video generation understanding, semantic and spatial reasoning, state tracking, causal consistency, physical constraints, and low-latency feedback. Develop unified generation-understanding architectures and closed-loop generation, understanding, control, and feedback systems with Agent and reinforcement learning teams. Validate interactive capabilities in game scenarios, establish evaluation systems, track industry advances, and define technical roadmaps.

Develop and enhance optimization-based models for European electricity markets. Analyze generation economics, transmission constraints, renewable integration, storage, fuel markets, emissions costs, and market outcomes using linear and mixed-integer programming. Conduct scenario analysis, manage large datasets, improve analytical methodologies, communicate model insights, monitor regulatory developments, and support client engagements through presentations and bespoke research.

Develop and maintain cloud data pipelines, ETL/ELT processes, warehouse schemas, semantic models, and integrations across internal and external data sources. Own pipeline reliability, monitoring, performance, and data quality while supporting governance, security, documentation, and DevOps practices. The role also supports BI analysts and managers, promotes consistent data practices, and helps improve team capabilities using Microsoft Fabric, Power BI, SQL, Python, and PySpark.

Build and scale Base360.ai’s short-term rental platform across frontend, backend, integrations, automation, dashboards, and AI-powered workflows. Work directly with customers, founders, and designers to identify problems, ship end-to-end solutions, and improve product outcomes. Develop reliable APIs, event-driven automations, cloud infrastructure, and integrations with Airbnb, Stripe, Twilio, OpenAI, and other platforms. Own features from discovery through deployment while balancing usability, security, scalability, and maintainability.

Build and scale Base360.ai’s short-term rental platform across frontend, backend, integrations, automation, AI workflows, dashboards, and customer-facing features. Own products end to end, from understanding customer problems through deployment and iteration. Develop reliable APIs and integrations with Airbnb, Stripe, Twilio, OpenAI, and other partners while improving usability, scalability, security, and operational outcomes.

Build and scale Base360.ai’s short-term rental platform, including customer-facing applications, APIs, automation engines, AI-powered workflows, third-party integrations, and cloud infrastructure. Develop systems for reservations, pricing, payments, guest communication, property operations, reporting, and financial workflows. Own projects end to end, make architectural decisions, ensure reliability, and deliver scalable products in a remote-first startup environment.

Designs, builds, and operates scalable full-stack telecom platforms. Responsibilities include architecture, backend and frontend development, infrastructure as code, testing, deployment, observability, code and architecture reviews, production readiness, partner oversight, and collaboration with AI/ML, DevOps, infrastructure, and product teams.

Analyze daily trading P&L, positions, risk reports, limits, and market risks for gas and other commodity desks. Support product approvals, risk committees, audits, trading procedure compliance, and Endur system changes. Enhance reporting and automate risk processes using Excel, VBA, SQL, Python, machine learning, and artificial intelligence while communicating findings to senior management and stakeholders.

Leads and grows ASOS’s AI engineering team, setting technical direction and engineering standards while remaining hands-on. Designs, builds, deploys, and supports production agentic AI and automation solutions integrated with finance and commercial systems. Owns delivery, operational readiness, monitoring, incident response, stakeholder engagement, and benefits tracking. Requires experience with agent frameworks, LLMs, automation, cloud deployment, software or data engineering, and engineering leadership.

Own web compatibility triage and incident response across DuckDuckGo browsers on Mac, Windows, iOS, and Android. Debug complex web applications and third-party code, distinguish site, browser, and privacy-related issues, reverse-engineer obfuscated code, build durable cross-platform fixes, and develop automation and LLM agent tooling to reproduce and triage breakage. Lead ambiguous projects independently and communicate with technical and non-technical stakeholders.

Own product analytics across product lines by defining success metrics, analyzing user behavior and retention, supporting experimentation, and guiding product strategy. Build scalable data products, governed self-service analytics, and event taxonomies using SQL and dbt. Partner with Product, Engineering, Design, and Go-to-Market teams to connect product usage with commercial outcomes. Promote data literacy and apply AI and LLM tools to improve analytics workflows.

Lead the design, development, and deployment of scalable, production-grade machine learning systems for diverse clients. Define ML deployment standards, make architectural decisions, collaborate with technical and commercial teams, advise customers, and mentor junior engineers. The role requires strong Python and software engineering expertise, experience operationalizing TensorFlow or PyTorch models, cloud architecture, security, infrastructure, Docker, and Kubernetes.

Monitor product functionality, analyze and query data, build dashboards, provide management information, and support cross-functional decision-making. The role owns reporting processes, develops operational controls, investigates issues, and automates recurring analysis using SQL and Python. It also maintains coding and visualization standards, reviews other analysts’ SQL, and communicates data-driven insights to stakeholders across Finance, Operations, Product, and Engineering.

Serve as a technical advisor to high-growth companies building products with Claude. Partner with engineering teams through pair programming, architecture reviews, code contributions, prototypes, evaluation frameworks, documentation, and scalable AI application design. Create developer resources, identify cross-engagement patterns, support hackathons and workshops, and collaborate with Anthropic’s product and engineering teams. The role requires production LLM application experience, strong Python skills, customer-facing communication, and travel to customer sites.