{"id":126072,"url":"https://alion.io/job/wintermute-machine-learning-researcher","title":"Machine Learning Researcher","company":{"id":60,"name":"Wintermute","domain":"wintermute.com","url":"https://alion.io/company/wintermute","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"A","score":95,"open_postings":16,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":376,"computed_at":"2026-10-16T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"DeFi","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"C++","optional":true},{"name":"CUDA","optional":true},{"name":"CUDA Toolkit","optional":true}],"status":"live","first_seen_at":"2025-11-18T13:05:13Z","employer_posted_date":"2025-11-18","last_verified_at":"2026-10-16T23:40:27Z","board_verified":true,"closed_at":null,"days_open":332,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":331},"description":"About Wintermute\nWintermute 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.\nWintermute 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.\nWorking at Wintermute\nYou 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.\nYou 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.\nResponsibilities:\nDevelop ML-based alpha generation models using high-frequency order book and market microstructure data.\n\nDesign and maintain data pipelines, preprocessing, and feature extraction workflows tailored to streaming tick data.\n\nResearch and implement advanced deep learning architectures for short-horizon forecasting and signal extraction.\n\nCollaborate with quant researchers and developers to integrate models into live trading environments.\n\nOptimise inference latency and robustness; ensure models behave safely under live market conditions.\n\nContinuously refine model quality through systematic backtesting, live evaluation, and monitoring.\n\nHard Skills Requirements:\nDegree in Computer Science, Machine Learning, Applied Mathematics, or similar quantitative discipline.\n\nStrong programming skills in Python and familiarity with ML libraries.\n\nProven track record applying ML/DL to real-world problems.\n\nFamiliarity with time-series modeling, signal extraction, or high-frequency data.\n\nExperience in developing ML infrastructure (data pipelines, experiment tracking, versioning).\n\nNice to have requirements:\nExperience in finance, trading, or quantitative research (not required).\n\nPublications, competition results (e.g., Kaggle, academic ML contests), or open-source contributions.\n\nFamiliarity with C++, CUDA, or low-latency systems.\n\nHere is why you should join our dynamic team:\nOpportunity to work at one of the world's leading algorithmic trading firms.\n\nEngaging projects offering accelerated responsibilities and ownership compared to traditional finance environments.\n\nA vibrant working culture with team meals, festive celebrations, gaming events and company wide team building events.\n\nA 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.\n\nGreat company culture: informal, non-hierarchical, ambitious, highly professional with a startup vibe, collaborative and entrepreneurial.\n\nA performance-based compensation with a significant earning potential alongside standard perks like pension and private health insurance.\n\nNote:\nAlthough we are unable to accept fully remote candidates, we support significant flexibility about working from home and working hours.\n\nWe offer UK work permits and help with 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