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G-Research

Quantitative finance research applying rigorous methods

Machine Learning Engineer Intern

Applied Machine LearningConfirmed live in the last 24 hours
Internship · Summer 2027London, UKNo salary listed

About the Job

Requirements

  • Be a current undergraduate, master's, or PhD student in machine learning or a related discipline.
  • Have strong object-oriented programming skills.
  • Have excellent machine learning reasoning skills and the ability to develop models when standard approaches are insufficient.
  • Work independently and collaboratively in small teams on engineering challenges, with a focus on machine learning and scientific computing.

Responsibilities

  • Implement ideas from published research papers.
  • Write custom libraries to efficiently train models on petabytes of data.
  • Reduce model training times by hand-optimising machine learning operations.
  • Profile custom machine learning architectures to identify performance bottlenecks.
  • Evaluate the latest hardware and software in the machine learning ecosystem.
  • Use off-the-shelf tools and custom solutions to advance quantitative research.

Desired Qualifications

  • Experience working with Python, PyTorch, and NumPy.
  • Experience in one or more of advanced optimisation methods, modern machine learning techniques, high-performance computing, profiling, or model inference.

About the Company

G-Research

Quantitative finance research applying rigorous methods

G-Research applies scientific rigour to solve complex challenges in financial markets. It brings together world-class researchers and engineers to develop data-driven models and trading ideas, testing them through rigorous experimentation and robust infrastructure. Unlike many traditional asset managers, its culture emphasizes deep exploration, reproducibility, methodical execution, and long-term thinking. The goal is to generate alpha through disciplined, evidence-based research that informs investment decisions and advances understanding of financial markets.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
London, United Kingdom
Founded
2001

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