ML Researcher — Flexible Hours for Crypto Alpha Signals

Wintermute; Greater London; On-site; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Pension

Private health insurance

Central London office with amenities

Job summary

Wintermute, a leading technology unicorn in crypto trading, seeks an experienced ML engineer to build alpha signal pipelines from ingestion to deployment. You will work with trading and infrastructure teams to create models using high-frequency order book data, stream processing, and feature extraction.

The role focuses on developing ML architectures for short-horizon forecasting, optimizing latency, and ensuring robust performance in live market conditions, with strong emphasis on backtesting

Qualifications

• Strong programming skills in Python and ML libraries.
• Experience applying ML/DL to real-world problems.
• Familiarity with time-series modeling and high-frequency data.
• Experience developing ML infrastructure (data pipelines, experiment tracking).

Responsibilities

• Develop ML-based alpha generation models using high-frequency data.
• Design and maintain streaming data pipelines and feature extraction workflows.
• Research and implement deep learning architectures for short-horizon forecasting.
• Collaborate with quant researchers to integrate models into live trading.
• Optimize inference latency and robustness for live markets.
• Refine model quality via backtesting and live evaluation.

Skills

Python

ML libraries

Time-series modeling

Data pipelines

Backtesting

Tools

CUDA

C++

Job description

Wintermute, a leading technology unicorn in crypto trading, seeks an experienced ML engineer to build alpha signal pipelines from ingestion to deployment. You will work with trading and infrastructure teams to create models using high-frequency order book data, stream processing, and feature extraction.

The role focuses on developing ML architectures for short-horizon forecasting, optimizing latency, and ensuring robust performance in live market conditions, with strong emphasis on backtesting