Machine Learning Researcher

About Wintermute  Wintermute is a technology unicorn and one of the largest algorithmic trading companies, specialising in digital assets. We provide liquidity across most cryptocurrency exchanges and trading platforms, a broad range of OTC trading solutions as well as supporting high profile blockchain projects and traditional financial institutions moving into crypto. Wintermute also has a Wintermute Ventures arm that invests in early stage DeFi projects.Wintermute was founded in 2017 and has successfully navigated industry cycles. Culturally, we combine the best of the two worlds: the technology standards of high-frequency trading firms in traditional markets and the innovative and entrepreneurial culture of technology startups. At Wintermute, we believe in the innovative potential of blockchain, the fundamental innovations, we have a long-term view on the digital asset market and are taking a leadership position in building an innovative and compliant market. You can read more 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.

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Design and maintain data pipelines, preprocessing, and feature extraction workflows tailored to streaming tick data.

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Research and implement advanced deep learning architectures for short-horizon forecasting and signal extraction.

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Collaborate with quant researchers and developers to integrate models into live trading environments.

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Optimise inference latency and robustness; ensure models behave safely under live market conditions.

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Continuously refine model quality through systematic backtesting, live evaluation, and monitoring. Hard Skills Requirements: •

Degree in Computer Science, Machine Learning, Applied Mathematics, or similar quantitative discipline.

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Strong programming skills in Python and familiarity with ML libraries.

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Proven track record applying ML/DL to real-world problems.

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Familiarity with time-series modeling, signal extraction, or high-frequency data.

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Experience in developing ML infrastructure (data pipelines, experiment tracking, versioning). Nice to have requirements: •

Experience in finance, trading, or quantitative research (not required).

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Publications, competition results (e.g., Kaggle, academic ML contests), or open-source contributions.

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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.

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Engaging projects offering accelerated responsibilities and ownership compared to traditional finance environments.

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A vibrant working culture with team meals, festive celebrations, gaming events and company wide team building events.

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A Wintermute-inspired office in central London, featuring an array of amenities such as table tennis and foosball, personalized desk configurations, a cozy team breakout area with games.

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Great company culture: informal, non-hierarchical, ambitious, highly professional with a startup vibe, collaborative and entrepreneurial.

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A performance-based compensation with a significant earning potential alongside standard perks like pension and private health insurance. Note: •

Although we are unable to accept fully remote candidates, we support significant flexibility about working from home and working hours.

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We offer UK work permits and help with relocation.