Machine Learning Engineer: Scalable ML/HPC for Finance

G-Research; Greater London; On-site; GBP 85,000 - 130,000; Full time

Benefits offered by this job

Highly competitive compensation

Annual discretionary bonus

Lunch provided via Just Eat

30 days’ annual leave

9% company pension contributions

Informal dress code

Comprehensive healthcare

Cycle-to-work scheme

Monthly company events

Job summary

A premier quantitative research firm in Greater London is seeking an exceptional Machine Learning Engineer to join their ML and HPC Architecture team. The successful candidate will work independently and collaboratively to tackle engineering challenges, designing systems that support high-impact research initiatives. Key responsibilities include optimising model inference, evaluating ML hardware, and working alongside experts to leverage cutting-edge technologies in machine learning. A postgraduate degree in ML or significant experience in data science is required, with a strong emphasis on effective communication skills.

Qualifications

• Experience building ML models at scale is a plus.
• Demonstrable track record of success in online data science competitions (e.g., Kaggle).
• Ability to apply advanced optimisation methods and profiling expertise.

Responsibilities

• Shape platforms and tools that drive research.
• Identify and work with cutting-edge machine learning tools.
• Collaborate across disciplines on varied initiatives.

Skills

Object-oriented engineering skills

Experience in Python

Knowledge of PyTorch

Knowledge of NumPy

Advanced optimisation methods

Modern ML techniques

HPC experience

Excellent communication skills

Education

Postgraduate degree in machine learning or related field

Job description

A premier quantitative research firm in Greater London is seeking an exceptional Machine Learning Engineer to join their ML and HPC Architecture team. The successful candidate will work independently and collaboratively to tackle engineering challenges, designing systems that support high-impact research initiatives. Key responsibilities include optimising model inference, evaluating ML hardware, and working alongside experts to leverage cutting-edge technologies in machine learning. A postgraduate degree in ML or significant experience in data science is required, with a strong emphasis on effective communication skills.