Machine Learning Researcher

Join Wintermute as a Machine Learning Researcher in London, focusing on developing alpha signal generation models for algorithmic trading.

Wintermute is a technology unicorn and one of the largest algorithmic trading companies, specializing in digital assets.

We provide liquidity across most cryptocurrency exchanges and trading platforms, support high-profile blockchain projects, and invest in early-stage DeFi projects.

Founded in 2017, we combine high-frequency trading standards with a startup culture.

## What you'll do

• •Develop ML-based alpha generation models using high-frequency order book and market microstructure data.
• •Design and maintain data pipelines, preprocessing, and feature extraction workflows.
• •Research and implement advanced deep learning architectures for forecasting and signal extraction.
• •Collaborate with quant researchers and developers to integrate models into live trading environments.
• •Optimize inference latency and robustness; ensure models behave safely under live market conditions.
• •Continuously refine model quality through systematic backtesting, live evaluation, and monitoring.

## Conditions

• •Opportunity to work at one of the world's leading algorithmic trading firms.
• •Engaging projects with accelerated responsibilities and ownership.
• •Vibrant working culture with team meals, festive celebrations, and gaming events.
• •Wintermute-inspired office in central London with amenities like table tennis and foosball.
• •Performance-based compensation with significant earning potential.
• •Standard perks like pension and private health insurance.
• •UK work permits and relocation support.

• •Degree in Computer Science, Machine Learning, Applied Mathematics, or similar quantitative discipline.
• •Strong programming skills in Python and familiarity with ML libraries.
• •Proven track record applying ML/DL to real-world problems.
• •Familiarity with time-series modeling, signal extraction, or high-frequency data.
• •Experience in developing ML infrastructure (data pipelines, experiment tracking, versioning).