Top Python Jobs in London

FPGA Engineers at Citadel Securities design and deploy FPGA solutions to enhance trading systems, maximizing efficiency and performance.

The Site Reliability Engineer will provide support and diagnose issues within a real-time, distributed environment, focusing on large-scale application and infrastructure management, with basic required skills in UNIX/Linux, networking, SQL, and scripting languages.

Build and extend high-scale egress-path systems running on Linux kernel and network dataplanes. Work on kernel network stack (eBPF), routing (BGP), and distributed systems to optimize packet flow, reliability, and performance. Collaborate across teams and participate in on-call rotation.

Own production NLP and applied AI systems that enrich scientific literature with entities, classifications, claims, and summaries. Design and evaluate classical NLP, embedding, retrieval, and LLM approaches; build scalable Python pipelines; manage cost, concurrency, reliability, and model quality. Collaborate with data engineers on Airflow and Dagster orchestration, contribute to agentic AI applications, and work with editors, product managers, and engineers to deliver research intelligence to users.

Build and operate NLP enrichment pipelines over scientific literature, extracting entities, classifications, claims, and summaries. Compare classical NLP, retrieval, embedding, LLM, and fine-tuned model approaches using evaluations, cost, quality, and operational metrics. Create golden datasets, define evaluation strategies, contribute to agentic AI applications, and collaborate with editors, product managers, engineers, SMEs, and vendors to deliver production modeling systems.

Build and operate production AI systems for go-to-market teams, including account segmentation, scoring, enrichment, buying-signal detection, agentic workflows, prospect research, outbound personalization, call summarization, and CRM hygiene. Own solutions end to end from design through deployment, while optimizing quality, latency, cost, reliability, evaluation, monitoring, and guardrails. Collaborate closely with Marketing, Sales, RevOps, and system users to deliver measurable commercial impact.

Build Paddle’s data science function and production decisioning systems from the ground up. Prioritize high-value use cases, personally deliver the first ML or agentic system, and own deployment, monitoring, experimentation, reliability, governance, and financial impact. The role will establish the production ML stack, collaborate across Product, Engineering, Risk, Finance, and Compliance, then hire and lead data scientists and ML engineers. Experience with regulated transactional domains, production ML operations, experimentation, and executive stakeholder management is required.

Build and operate Kraken’s internal AI platform, including governed integrations, authentication, internal tooling, evaluation systems, spend controls, identity and access controls, provisioning, vendor configuration, and policy enforcement. Provide technical enablement through documentation, deep dives, and office hours while supporting teams and administering the enterprise AI estate.

As a Senior DevSecOps Engineer, you will integrate security into CI/CD processes, design security tooling, implement policy-as-code, and champion secure engineering practices.

Lead and contribute to building scalable, production-grade data systems for private markets. Architect end-to-end data workflows supporting analytics and AI/ML, ensure observability, testing, and operational maturity, influence technical strategy, engage senior stakeholders, and manage and mentor software engineers while partnering with product, data science, and business teams.

Serve as a technical sales resource for UK commercial accounts by building customer relationships, leading technical discovery, presentations, demonstrations, workshops, and proof-of-concepts. Partner with sales managers to achieve technical wins, validate solutions, support buying decisions, and drive product adoption. Maintain current Splunk expertise and opportunity updates in Salesforce while advising customers on integrations, infrastructure, security, observability, and data solutions.

Build and optimize distributed foundation-model training infrastructure across multi-node GPU clusters. Profile data pipelines, GPU kernels, memory, networking, and CPU/GPU workloads to improve convergence speed and utilization. Develop CUDA, cuDNN, Triton, and custom kernel solutions integrated with PyTorch. Create monitoring and debugging tools for large-scale training runs and diagnose performance issues.

Build and maintain the software engineering backbone of Genesis-World, an open-source robotics simulation platform. Responsibilities include scalable testing for JIT-compiled engines, deterministic reproduction and serialization, autodiff infrastructure, scene editing, extensible plugins, robot actuation, event systems, timing architecture, refactoring, performance optimization, and cross-platform debugging. The role also involves code review, issue triage, contributor support, and collaboration with compiler and physics teams.

Develop and optimize learning-based robotic manipulation and locomotion systems. Build low-latency teleoperation infrastructure, train reinforcement and imitation learning policies, deploy policies to real robots, diagnose control-pipeline bottlenecks, and reduce the simulation-to-real-world gap through simulation and hardware co-optimization.

Own Quadrants, an open-source Python compiler for performance-critical numerical computing. Responsibilities include API design, intermediate representation and lowering, multi-backend support, compiler optimization, GPU kernel development, numerical primitives, benchmarking, regression tracking, and roadmap ownership. The role combines GPU programming, compiler engineering, Python API design, performance optimization, user engagement, and open-source product direction, with potential to lead a small team.

Designs and maintains foundational frameworks, internal tools, and reusable systems that accelerate AI research and engineering workflows. Collaborates across teams to validate use cases, simplify complex requirements, improve development processes, and reduce organizational friction. Responsibilities include identifying code design flaws, implementing large-scale changes, conducting code reviews, documenting practices, training teams, and maintaining high software quality.

Develop and ship production-ready physics simulation capabilities for Genesis-World, improving speed, fidelity, scalability, completeness, and solver coupling. Implement physics algorithms in Python using the Quadrants compiler across CPU and GPU backends. Validate methods through analytical solutions, cross-engine comparisons, and real-world data while supporting robotics and physical AI pipelines.

Own Quadrants, an open-source Python compiler for high-performance physics and numerical computing. Lead its API, IR, lowering, compiler optimizations, GPU and CPU backends, numerical primitives, benchmarks, and roadmap. Improve kernel performance, usability, correctness, and extensibility while partnering with Genesis users and the broader open-source community. The role combines GPU programming, compiler engineering, Python API design, performance analysis, and technical leadership, with potential to grow into managing a small team.

Design and deploy machine learning models for financial document processing, optimize large language models, collaborate with cross-functional teams, and guide junior peers in a fast-paced environment.

Senior security researcher responsible for large-scale data collection and analysis, operating and building honeypots, performing vulnerability research and reverse engineering, developing automated tooling and GenAI/LLM workflows, collaborating with intelligence teams, reproducing vulnerabilities, and publishing technical research.

Analyze and reconcile claims data from internal systems, TPAs, bordereaux, and data warehouses. Build SQL extracts, dashboards, KPI reports, reserve reviews, severity analyses, and executive reporting. Support underwriting and actuarial decisions through claims insights, loss development analysis, data quality investigations, and portfolio trends. Help develop claims rules, scoring models, exception reporting, and UAT test cases using SQL, Python, Azure Databricks, and related data platforms.

Work with power market data to build and deploy BESS revenue modelling features, maintain forecasts and data feeds, coach an AI analyst (Ko), and manage end-to-end product releases for regional customers.

Leads development, enhancement, governance, calibration, and validation of UK mortgage IRB credit risk models covering PD, LGD, and EAD. The role manages model lifecycle activities, back-testing, performance analysis, deficiency remediation, documentation, stakeholder engagement, and compliance with UK PRA Basel 3.1 requirements. It requires collaboration across credit, risk, business, and support functions, plus strong quantitative, regulatory, coding, communication, and project leadership skills.

Design, build, and maintain petabyte-scale batch and streaming data pipelines for robotics foundation model training and evaluation. Own data models, storage systems, ingestion, transformation, and orchestration infrastructure. Standardize processing across teleoperation and synthetic simulation datasets while operating production-grade distributed systems and infrastructure.

Leads full-stack software development for AI-enabled enterprise solutions, covering user experience, application logic, APIs, data integration, testing, and automation. The role advises business and IT leaders, resolves complex problems, shapes technology strategy, applies security and privacy principles, supports platform integration, and mentors engineers. It also requires mainframe application experience, broad multi-platform development expertise, stakeholder communication, and consulting capabilities.