Machine Learning Engineer

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 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: 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 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.

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