Machine Learning Researcher

About Wintermute 

Wintermute is a prominent crypto native algorithmic trading company specializing in digital assets. Our expertise lies in providing liquidity across various cryptocurrency exchanges, offering OTC trading solutions, and supporting blockchain projects and financial institutions venturing into the crypto space. Wintermute Ventures, our investment arm, specifically focuses on early-stage DeFi projects.

Established in 2017, Wintermute has adeptly maneuvered through industry cycles by combining the technological standards of high-frequency trading firms with the innovative and entrepreneurial spirit of technology startups. Embracing digital assets as more than just another asset class, we champion the potential of blockchain innovation with a forward-thinking approach to the market.

Working at Wintermute

We are searching for an experienced machine learning engineer or researcher adept in applied deep learning, particularly in fields involving high-frequency or large-scale time-series data.

Responsibilities:

• Development of alpha signal generation models using high-frequency order book and market microstructure data.
• Creation and maintenance of data pipelines, preprocessing, feature extraction workflows customized for streaming tick data.
• Research and implementation of advanced deep learning architectures for short-horizon forecasting and signal extraction.
• Collaboration with quant researchers and developers to seamlessly integrate models into live trading environments.
• Optimization of inference latency and reliability to ensure safe model behavior under live market conditions.
• Continuous enhancement of model quality through rigorous backtesting, live evaluation, and monitoring processes.

Hard Skills Requirements:

• Degree in Computer Science, Machine Learning, Applied Mathematics, or similar quantitative discipline.
• Proficiency in Python programming and familiarity with ML libraries.
• Strong proven track record in applying ML/DL to practical challenges.
• Knowledge of time-series modeling, signal extraction, or high-frequency data.
• Experience in building ML infrastructure like data pipelines, experiment tracking, and versioning.

Nice to have requirements:

• Background in finance, trading, or quantitative research.
• Notable publications, competition results (e.g., Kaggle, academic contests), or contributions to open-source projects.
• Familiarity with C++, CUDA, or low-latency systems.

Reasons to join our dynamic team:

• Opportunity to work at a leading algorithmic trading firm globally.
• Engaging projects with increased responsibilities and ownership compared to mainstream finance roles.
• Lively working culture with team meals, festive celebrations, gaming events, and company-wide team-building activities.
• State-of-the-art Wintermute-inspired office in central London, offering various amenities such as table tennis, foosball, personalized desk setups, and a cozy team breakout area with games.
• Exceptional company culture characterized by informality, non-hierarchy, ambition, professionalism, startup ethos, collaboration, and entrepreneurship.
• Performance-based compensation with high earnings potential and standard benefits like pension and private health insurance.

Note:

• While we are unable to consider fully remote candidates, we offer flexibility in terms of working from home and working hours.
• We provide UK work permits and relocation assistance to eligible candidates.