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Machine Learning EngineerG-ResearchLondon, England, United Kingdom

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Machine Learning Engineer

G-Research
  • GB
    London, England, United Kingdom
  • GB
    London, England, United Kingdom

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Machine Learning Engineer
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Talent Acquisition Specialist at G-Research - Engineering 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.
The role 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
Evaluating alternative accelerators for ML workloads
Multi‑node distributed training to understand trade‑offs in networking technology
Optimising model inference to minimise latency or maximise throughput
Understanding and optimising different storage technology to maximise bandwidth
Evaluating the latest hardware and software in the machine learning ecosystem
Liaising with vendors and providing constructive feedback on their products and roadmaps
Who are we looking for? 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:
A postgraduate degree in ML or a related field, or bringing commercial experience building ML models at scale – we will also consider exceptional candidates with a demonstrable track record of success in online data‑science competitions, such as Kaggle
Strong object‑oriented engineering skills, with experience in Python, PyTorch and NumPy desirable
The ability to apply advanced optimisation methods, modern ML techniques, HPC, profiling or model‑inference expertise; you do not need to have all of the above
A passion for the latest ML and HPC trends, with genuine curiosity and enthusiasm
Excellent communication skills with the ability to work independently, engage with vendors, explore new technologies and present results effectively to stakeholder
Choose the right level of abstraction, using quick one‑off scripts for proofs of concept or designing more complex systems when needed
Finance experience is not necessary for this role and candidates from non‑financial backgrounds are encouraged to apply.
Benefits
Highly competitive compensation plus annual discretionary bonus
Lunch provided (via Just Eat for Business) and dedicated barista bar
30 days’ annual leave
9% company pension contributions
Informal dress code and excellent work/life balance
Comprehensive healthcare and life assurance
Monthly company events
Seniority level Not Applicable
Employment type Full‑time
Job function Information Technology, Engineering, and Finance
Industries Financial Services and Capital Markets
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  • London, England, United Kingdom

Compétences linguistiques

  • English
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