Jobs at G-Research

Twelve-week software engineering internship developing production-level code, research platforms, data-processing pipelines, database queries, and internal tools supporting quantitative finance research. Interns collaborate with quantitative researchers and experienced engineers, contribute to scalable systems, and receive structured onboarding, mentoring, and technical development opportunities.

Build and lead the Platform Desktop Engineering team, owning service availability, security, performance, support, roadmap, provisioning, image builds, automation, monitoring, hardware lifecycle, capacity, and budget. The role requires hands-on Linux expertise, production service ownership, enterprise security judgment, stakeholder management, and collaboration across infrastructure, security, identity, support, and HR teams.

Maintain the Linux desktop platform, including OS image build pipelines, provisioning tooling, security, monitoring, hardware lifecycle, and system health. Troubleshoot bare-metal and virtual machine provisioning across OpenStack and Ironic, support technical users, manage incidents and changes, and contribute to capacity planning. The role requires strong Linux administration, Python scripting, infrastructure automation, security, diagnostics, and communication skills.

Recruit exceptional software engineering talent through proactive sourcing, market mapping, networking, referrals, and relationship-building. The role manages long-term talent pipelines, partners with engineering leaders and hiring managers, champions candidates, informs recruitment strategy, and contributes to employer branding and candidate experience improvements.

Design, build, and optimize scalable software platforms supporting quantitative research and financial trading. Responsibilities include developing trading systems, modeling and simulation frameworks, research tools, machine-learning infrastructure, and high-performance distributed systems. The role involves collaborating with quantitative researchers, owning solutions end to end, applying strong software fundamentals, improving scalability and performance, and evaluating emerging technologies.

Own the reliability, performance, resilience, observability, automation, and security of enterprise network infrastructure. Design and maintain Cisco and Arista datacenter networks, support WAN connectivity, automate operations with Python and Ansible, extend infrastructure-as-code and CI/CD practices, and lead incident response, on-call operations, postmortems, and root-cause analysis for complex network issues.

As an Observability Engineer, you'll design systems for telemetry management, build scalable pipelines, and contribute to industry observability standards. Responsibilities include extending OpenTelemetry and enhancing incident response with telemetry data.

Lead and grow a team of infrastructure engineers responsible for core services (TFE, AD, Jenkins, inventory tooling, bastions). Set technical direction, ensure reliability and performance, drive IaC and automation (including AI-driven initiatives), act as incident escalation, balance ops with long-term improvements, hire and develop staff, and represent the team's roadmap to stakeholders.

Operate and evolve foundational infrastructure services including Terraform Enterprise, Active Directory, Jenkins and self-hosted platforms. Automate provisioning and lifecycle management, ensure monitoring, backups and recoverability, collaborate with platform and application teams, and participate in on-call incident response and continuous improvement.

Lead and shape the Adversary Emulation (internal Red Team) programme: plan and run complex offensive security operations, provide technical leadership and stakeholder reporting, develop tooling and team capabilities, and coach team members to improve organisational security outcomes.

Lead the Strategic Planning Office to define and execute long-term strategy, own the three-year plan and AOP, set and track OKRs, drive governance and QBRs, advise senior leadership, and build a high-performing strategic planning function that improves organisational effectiveness using data and emerging technologies.

Lead the strategy, architecture and operation of the firm's IAM platforms. Own authentication, authorization, identity lifecycle, access governance and developer identity services. Build and mentor an IAM engineering team, drive automation, modernise identity services, define standards (MFA, RBAC/ABAC, PAM), and partner with engineering, security, risk and audit to ensure secure, scalable and auditable identity controls.

The role requires leveraging financial knowledge and analytical skills to develop mathematical models predicting financial market movements, utilizing strong quantitative and computing skills in research.

The role involves developing and optimizing machine learning models and collaborating on research projects with quantitative researchers.

Join as a Database Platform Engineer to design, build, and operate critical database platforms, ensuring high availability and performance in a collaborative environment.

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.

The role involves developing an ML research and deployment pipeline, implementing best practices in model and feature management, and ensuring robustness in production through effective solutions and collaboration.

Conduct research using machine learning techniques to develop investment strategies, leveraging extensive data and computational resources.

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

The role focuses on using advanced statistical and ML techniques to analyze financial market data and generate predictive insights.