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Paid Internship
Work Mode
Time Spent
Required Degree
Duration

12Open Positions

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Architecture and Innovation Software Engineer Intern

G-Research
Found 2 months ago
Location
London, United Kingdom
Time
Full-time
Work Mode
On-site
Salary
Highly competitive compensation
Visa Help
Not disclosed
Last Verified
2 months ago

Education

  • Bachelor

Skills & Qualifications

Technical Skills

  • Python
  • Rust
  • C++
  • C#
  • Java
  • machine learning
  • HPC
  • distributed computing

Soft Skills

  • Clear communication
  • initiative
  • rigour
  • collaborative mindset

Job Description

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. 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.

Requirements

  • 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

Related Field

  • Software Engineering

Related Subfield

  • AI/ML/GenAI Engineering

Languages

  • English

Nice to Haves

  • An appreciation of clean software design, data structures and systems thinking
  • A professional interest in quantitative finance or financial systems
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