Machine Learning Researcher
Wintermute
- London, England, United Kingdom
- London, England, United Kingdom
Über
Founded in 2017, Wintermute has successfully navigated industry cycles. Culturally, we combine the best of high‑frequency trading technology standards in traditional markets with the innovative and entrepreneurial culture of technology startups. For Wintermute, digital assets are not just another asset class; we believe in the innovative potential of blockchain and take a leadership position in building an innovative and compliant market.
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 another 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 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 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 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 around working from home and working hours.
We offer UK work permits and help with relocation.
Key Skills
Intelligence Community Experience
Python
SPSS
Microsoft Word
R
Regression Analysis
Windows
Stata
Microsoft PowerPoint
Research Experience
Data Modeling
Writing Skills
Employment Type: Full‑Time
Experience: years
Vacancy: 1
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Sprachkenntnisse
- English
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