Machine Learning Engineer

Goliath Partners; Greater London; Hybrid; GBP 250,000 - 450,000; Full time

Job summary

Goliaths is hiring a mid-level Machine Learning Engineer for its London office on a hybrid basis. The role collaborates directly with the CEO and a team of PMs to drive portfolio-wide alpha through foundational modelling and LLM-assisted efforts across equities, options & futures.

The candidate should have deep ML experience, Python proficiency, C++17 knowledge, and a track record of research publications in related modelling domains. DOE compensation is substantial."

Qualifications

• Interest in the financial space; degrees in maths, statistics, OR, econometrics, or internships/project work in finance.
• Extensive experience in Machine Learning.
• Core understanding of Python.
• Publications and experience in foundational modelling.
• Prior knowledge of C++17.
• Currently working as a Research Engineer.

Skills

Machine Learning

Python

C++17

Research publications

Foundational modelling

Finance domain knowledge

Job description

A forward thinking investment firm of Goliaths is hiring a mid-level Machine Learning Engineer in their London office on a hybrid basis. Firm is 1-3 days on-site and is willing to wait for full non-compete terms of up to 24~ months for the correct person.

The role will be reporting directly into the CEO (team of 40 PMs) and will consist of portfolio-wide alpha impact using foundational modelling for order flow & LLMs to accelerate efforts across equities, options & futures.

Essential skills

• Interest in the financial space (ideally internships, commercial experience or personal projects built to date). Alternatively mathematics, statistics, ops research or econometrics related degree.
• Extensive experience in Machine Learning.
• Core understanding of Python.
• Research publications & experience in foundational modelling.
• Prior knowledge of C++17.
• Working in the capacity of a 'Research Engineer' currently.

Compensation

Our client is looking at offering £250,000-450,000 for this person DOE.