Quantitative Developer - Machine Learning Strategies - Trading Desk

Paragon Alpha - Hedge Fund Talent Business; Greater London; On-site; GBP 85,000 - 130,000; Full time

Job summary

Paragon Alpha is seeking an experienced Quantitative Developer to join a systematic equities trading team. You will develop and deploy ML models on high-frequency market data and collaborate with portfolio managers to translate research into live signals.

The role blends machine learning, quantitative research, and production engineering. You will optimize models, scale compute, and build workflows from research to deployment, with strong Python and Linux skills; C++ is a plus.

Qualifications

• 3+ years of experience in software engineering, quantitative development or similar computational role.
• Strong Python skills and experience with large, complex datasets.
• Experience with distributed computing and Linux; C++ is a strong advantage.

Responsibilities

• Develop and deploy ML models on high-frequency market data.
• Collaborate with portfolio management to translate research into live trading signals.
• Improve workflows, scaling and production readiness from research to deployment.

Skills

Python

Machine Learning

Distributed Computing

Linux

C++

Job description

We're working with a trading pod at a leading global hedge fund looking for an experienced Quantitative Developer to join a systematic equities trading team.

The role sits at the intersection of machine learning, quantitative research and systematic trading, developing and deploying ML models on high-frequency market data and working closely with portfolio management to turn research into live trading signals.

You'll develop and optimise classical and deep learning models, improve distributed computing and large-scale parameter searches, and build efficient workflows from research through to production.

We're looking for someone with 3+ years' experience in software engineering, quantitative development or a similar computational role, with strong Python skills and experience working with large, complex datasets. Experience with distributed computing and Linux is important, while C++ would be a strong advantage.

This is the a unique chance to deploy ML models into systematic trading, and ensure your code and work directly generates profit.