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# Machine Learning Researcher

- **Company:** Wintermute
- **Location:** London, UK (Remote available)
- **Contract:** Permanent contract
- **Skills:** Algorithmic Trading, C++ (Programming Language), Nvidia CUDA, Computer Programming, Python (Programming Language), Machine Learning, Management of Software Versions, Feature Engineering, Data Ingestion, Deep Learning, Kaggle, Scikit Learn, Information Technology, Low Latency, Free and Open-Source Software, Machine Learning Operations, Feature Extraction, Data Pipelines
- **Published:** August 17, 2026
- **Apply:** https://www.efinancialcareers.com/jobs-United_Kingdom-London-Machine_Learning_Researcher.id24299807

## About the Role

quality through systematic backtesting, live evaluation, and monitoring. Hard Skills Requirements: 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). Nice to have requirements: Experience in finance, trading, or quantitative research (not required). Publications, competition results (e.g., Kaggle, academic ML contests), or open-source contributions. Familiarity with C++, CUDA, or low-latency systems. Here is why you should join our dynamic team: Opportunity to work at one of the world's leading algorithmic trading firms Engaging projects offering accelerated responsibilities and ownership compared to traditional finance environments. A

## Description

here. Working at Wintermute You are an experienced machine learning engineer or researcher with a strong track record in applied deep learning, ideally in domains involving high-frequency or large-scale time-series data. You will focus on developing alpha signal generation pipelines from data ingestion and feature engineering to model training and deployment, in collaboration with our trading and infrastructure teams. Responsibilities: 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 tailored to streaming tick data. Research and implement advanced deep learning architectures for short-horizon forecasting and signal extraction. Collaborate with quant researchers and developers to integrate models into live trading environments. Optimise inference latency and robustness; ensure models behave safely under live market conditions. Continuously refine model


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