Machine Learning Engineer

Barlowe LLP; Greater London; On-site; GBP 70,000 - 100,000; Full time

Benefits offered by this job

Highly competitive compensation

Lunch provided

30 days’ annual leave

9% company pension contributions

Comprehensive healthcare

Job summary

Barlowe LLP seeks a Machine Learning Engineer to join the ML and HPC Architecture team, based in London. This role involves working with cutting-edge technology, collaborating on various ML projects, and optimising processes to enhance performance across teams.

Ideal candidates will possess a postgraduate degree in Machine Learning or related experience, along with strong programming skills in Python and familiarity with ML model building. The role does not require finance experience, encouraging diverse applicants.

Qualifications

• Proven experience building ML models at scale.
• Strong object-oriented engineering skills.
• Ability to apply advanced optimisation methods.

Responsibilities

• Identify and work with cutting-edge machine learning tools.
• Collaborate with internal and external teams on ML initiatives.
• Evaluate alternative accelerators for ML workloads.

Skills

Python

Object-oriented engineering

ML model building

PyTorch

NumPy

Optimisation methods

Education

Postgraduate degree in ML or related field

Job description

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.

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
• 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.