Do you want to tackle the biggest questions in finance with near infinite compute power at your fingertips?
G-Research is a leading quantitative research and technology firm, with offices in London and Dallas. We are proud to employ some of the best people in their field and to nurture their talent in a dynamic, flexible and highly stimulating culture where world-beating ideas are cultivated and rewarded.
This is a role based in our new Soho Place office – opened in 2023 - in the heart of Central London and home to our Research Lab.
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
