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A leading quantitative finance firm in Greater London is seeking a Machine Learning Engineer to join their ML and HPC Architecture team. In this role, you will collaborate with various teams to leverage cutting-edge machine learning technologies, evaluate accelerators, and optimize model performance. The ideal candidate will have a postgraduate degree in ML or related experience, strong engineering skills, and a passion for the latest ML trends. The firm offers highly competitive compensation, generous annual leave, and an excellent work/life balance.
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.
We are looking for an exceptional Machine Learning Engineer to work in our ML and HPC Architecture team, identifying and working with tools at the cutting‑edge of machine learning.
You will work closely with a wide range of internal G-Research teams, including Quant Researchers, Quant ML engineers and other engineering groups - as well as with external partners and experts.
You will collaborate across disciplines on a broad set of initiatives to help G-Research leverage the next generation of machine‑learning technologies.
Past projects have included:
You will be comfortable working both independently and in small teams on a variety of engineering challenges, with a particular focus on machine learning and scientific computing.
The ideal candidate will have the following skills and experience:
Finance experience is not necessary for this role and candidates from non-financial backgrounds are encouraged to apply.