About The 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.

Take the next step in your career.

The role

We are looking for exceptional machine learning engineers to work alongside our quantitative researchers on cutting-edge machine learning problems.
As a member of the Core Technical Machine Learning team, you will be engaged in a mixture of individual and collaborative work to tackle some of the toughest research questions .
In this role, you will use a combination of off-the-shelf tools and custom solutions written from scratch to drive the latest advances in quantitative research.

Past projects have included

Implementing ideas from a recently published research paper
Writing custom libraries for efficiently training 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?

Candidates 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

Either a post-graduate degree in machine learning or a related discipline, or commercial experience working on machine learning models at scale. We will also consider exceptional candidates with a proven record of success in online data science competitions, such as Kaggle
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 ML reasoning and communication skills are crucial: off-the-shelf methods don’t always work on our data so you will need to understand how to develop your own models in a collaborative environment working in a team with complementary skills

Finance experience is not necessary for this role and candidates from non-financial backgrounds are encouraged to apply.
Why should you apply?

Highly competitive compensation plus annual discretionary bonus
Lunch provided (via Just Eat for Business) and dedicated barista bar
35 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