Top Tech Jobs & Startup Jobs in London

Design and develop core components of a distributed storage platform in Rust. Build scalable, resilient systems for large data workloads, collaborate with researchers and engineers on data-access needs, optimize Kubernetes services, integrate Kafka and streaming technologies, and contribute to architecture, testing, code quality, and operational excellence.

Design and develop core components of a distributed storage platform in Rust. Build scalable, resilient services for large data workloads, optimize systems running in Kubernetes, integrate Kafka-based event streaming, and contribute to distributed-systems architecture. Collaborate with researchers and engineers to understand data-access requirements while promoting testing, code quality, operational excellence, and clear technical communication.

Lead the Core AI team and its foundational platform, including GPU compute, model serving, developer tooling, secure AI-agent environments, and MCP services. Own the infrastructure roadmap, build-versus-buy decisions, sandboxing strategy, and developer adoption initiatives. Mentor product-focused engineers, influence senior stakeholders, collaborate with open-source teams, and drive scalable platform delivery across the firm.

The role involves developing machine learning models, optimising system performance, and collaborating with diverse teams on innovative projects.

G-Research seeks a Quantitative Researcher to use machine learning and statistical methods to analyze global financial markets. A Master's or PhD in a quantitative field is preferred, but prior finance experience is not necessary.

Build production data pipelines that transform third-party datasets into research-ready data and live signals. Partner with quantitative researchers to engineer features, develop signals, validate and normalize data, and use LLM-based agents to automate ingestion-to-signal workflows. The role also involves creating reusable tools that help researchers and data scientists scale their work.

Own recurring operational and productivity reporting, deliver ad hoc analysis for senior managers, support process redesign, maintain operational hygiene and resilience, identify emerging issues, and build relationships across technology teams.

Build, maintain, and evolve RHEL and Ubuntu platforms supporting quantitative research. Responsibilities include OS image creation, provisioning and lifecycle management, Ansible automation, Linux security hardening, vulnerability response, kernel and package remediation, observability, telemetry, APIs, databases, and agentic frameworks for autonomous operations. The role requires strong Linux expertise, programming ability, infrastructure automation skills, and collaboration.

Build and operate platform services, APIs, workflows, and data models for storage infrastructure. Automate capacity, tenant, quota, access, and data lifecycle processes with safe, auditable, idempotent changes. Develop tests, observability, and stable service contracts while troubleshooting production systems, responding to incidents, and participating in on-call rotation. Collaborate with users and partner teams to convert operational challenges into reliable engineering solutions.

Twelve-week machine learning internship focused on implementing research papers, building custom libraries for petabyte-scale model training, optimizing ML operations, profiling architectures, and evaluating emerging ML hardware and software. Interns will collaborate with quantitative researchers and engineers on advanced machine learning and scientific computing challenges.