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.
• 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 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 vibrant working culture with team meals, festive celebrations, gaming events and company wide team building events.
• 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.
• Great company culture: informal, non-hierarchical, ambitious, highly professional with a startup vibe, collaborative and entrepreneurial.
• 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.
• We offer UK work permits and help with relocation.