G-Research
Graduate Machine Learning Engineer
Get notified of more jobs like this · No spam, ever
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
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.
Role purpose
Start date: Tuesday 31st August 2028
We are looking for exceptional graduate machine learning engineers to work alongside our quantitative researchers on cutting-edge machine learning problems.
As a graduate within the Technical Machine Learning team, you will be engaged in a mixture of individual and collaborative work to tackle some of the toughest research questions.
You will also use a combination of off-the-shelf tools and custom solutions written from scratch to drive the latest advances in quantitative research.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Key Responsibilities
- Implementing ideas from published research papers
- Writing custom libraries to efficiently train models on petabytes of data
- Reducing model training times by hand optimising machine learning operations
- Profiling custom ML architectures to identify performance bottlenecks
- Evaluating the latest hardware and software in the machine learning ecosystem
Who are we looking for?
We are looking for graduates that 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 current undergraduate, master's or PhD student in machine learning or a related discipline
- Strong object-oriented programming skills and experience working with Python, PyTorch and NumPy are desirable
- Experience in one or more advanced optimisation methods, modern ML techniques, HPC, profiling, model inference; you don’t need to have all of the above
- Excellent machine learning reasoning skills, with the ability to develop your own models when standard approaches are insufficient
- Strong communication and collaboration skills, with the ability to work effectively in a team with complementary expertise
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Finance experience is not necessary for this role and candidates from non-financial backgrounds are encouraged to apply.
Why join us?
- 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
- Cycle-to-work scheme
- Monthly company events
G-Research is committed to cultivating and preserving an inclusive work environment. We are an ideas-driven business and we place great value on diversity of experience and opinions.
We want to ensure that applicants receive a recruitment experience that enables them to perform at their best. If you have a disability or special need that requires accommodation please let us know in the relevant section.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Location