We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity.
From our London HQ, we unite world-class researchers and engineers in an environment that values deep exploration and methodical execution - because the best ideas take time to evolve. Together we’re building a world-class platform to amplify our teams’ most powerful ideas.
As part of our engineering team, you’ll shape the platforms and tools that drive high-impact research - designing systems that scale, accelerate discovery and support innovation across the firm.
Take the next step in your career.
The role
- Dates: 30 March 2026 – 18 September 2026 or 29 June 2026 – 18 September 2026
- Working hours: 09:00–17:30
- Location: Central London
The Architecture and Innovation function at G-Research shapes the future of our technology landscape. As a Software Engineering Intern, you’ll join a team focused on solving complex systems problems, from machine learning performance on emerging hardware to optimising distributed computing across thousands of nodes.
Your work will span three core areas:
- Architecture Practice: collaborating with engineers and business stakeholders to evolve our technical roadmap and guide system design choices across on premise and cloud environments
- AI, ML and HPC: Researching and prototyping the use of next-generation, software, hardware and frameworks for cutting-edge research and high-performance computing
- Open-Source Software: contributing to open-source ML frameworks and engaging with the broader community to influence future development
We’re investing heavily in experimentation and benchmarking to identify the most promising technologies, with the end goal of integrating them seamlessly into the G-Research research stack.
As an intern, you’ll contribute to real-world projects such as:
- Prototyping and benchmarking machine learning models on emerging hardware accelerators
- Building working examples to evaluate model training speed, compatibility and performance
- Developing tools and pipelines that integrate novel technologies into our internal infrastructure
- Analysing gaps in new vendor technologies and collaborating with teams to close them
- Contributing to technical publications and internal knowledge-sharing on new ML hardware
- Matching research use cases to optimal compute strategies
You’ll gain an in-depth introduction to financial technology, access to tailored training resources and mentorship from experienced engineers throughout the programme.
Who are we looking for?
We are seeking pragmatic software engineers with a strong foundation in computer science and a curiosity for systems-level design.
You should be:
- On track for a 2:1 or above in Computer Science or a related discipline, graduating in 2027
- Experienced in an object-oriented programming language such as Python, Rust, C++, C# or Java
- Comfortable reasoning about system performance, benchmarking and architecture trade-offs
- Genuinely curious about the evolution of hardware and ML frameworks, and how they shape future capabilities
We’re also looking for:
- An appreciation of clean software design, data structures and systems thinking
- Clear communication, with the ability to adapt your message to technical and non-technical audiences
- Initiative and rigour in evaluating new approaches and surfacing well-reasoned recommendations
- A collaborative mindset and an interest in contributing to open-source communities
- A professional interest in quantitative finance or financial systems is a bonus but not required
Why should you apply?
- Highly competitive compensation
- 30 days’ holiday pro-rata
- 9% company pension contributions
- Opt-in private health insurance
- Monthly company events
- Informal dress code and excellent work/life balance
- Access to online learning resources and structured soft skills training
- Central London office close to five stations and six tube lines
Interview process
If your CV is shortlisted, you will be invited to complete a technical test. Candidates who pass will proceed to a series of technical and behavioural interviews.
