Wintermute hiring quant roles

Wintermute’s London jobs page is carrying four very specific openings at once: Algorithmic Trader, Machine Learning Researcher, Quant Researcher with a mid-frequency trading focus, and DeFi Algorithmic Trader. That is not a generic “we’re hiring” page; it is a map of where one of crypto’s biggest market makers thinks the next edge is. (jobs.lever.co) Wintermute describes itself as one of the largest algorithmic trading companies in digital assets, providing liquidity across major cryptocurrency exchanges and trading platforms. In plain English, that means it is one of the firms constantly posting buy and sell quotes so other people can trade without staring at an empty order book. (wintermute.com) The Algorithmic Trader role shows what that work looks like on the ground. Wintermute says the job starts with Python, large trading datasets, and projects that affect profit and loss directly after a short training period with the global trading team. (wintermute.com) That listing also says prior trading knowledge is not required, but curiosity about high-frequency trading and liquidity provision is. The company is screening for people who can code, think in probabilities, and learn market structure fast, not just people who already have a Wall Street résumé. (wintermute.com) The Machine Learning Researcher role points to a different problem: predicting what the market will do in the next few seconds from a firehose of tick-by-tick data. Wintermute says this person would build alpha-generation models from order-book data, engineer features, train deep learning systems, and then push those models into live trading. (wintermute.com) That matters because market making is no longer just “post a bid and ask and collect the spread.” The firm is explicitly asking for short-horizon forecasting, signal extraction, inference latency work, and live monitoring, which is the language of teams trying to predict flow before it hits them. (wintermute.com) The Quant Researcher role gets even more specific by naming mid-frequency trading, which Wintermute defines as strategies with holding times above 10 seconds and up to days. That sits between ultra-fast market making and slow discretionary investing, and it tells you the firm wants models that can survive longer than a blink but still react faster than most human traders. (wintermute.com) Wintermute says that researcher would use high-resolution market data to find short-term alpha signals, run backtests and simulations, and adapt strategies from traditional finance into crypto. In other words, the company is treating crypto less like a side bet and more like another venue where mature quant methods can be ported, tested, and scaled. (wintermute.com) The DeFi Algorithmic Trader opening adds one more clue. Wintermute says that team works on “on-chain searching,” trading strategies, and the backend systems that power the trading engine, with requirements including Python, Rust, or Go, plus knowledge of the Ethereum Virtual Machine and smart-contract tooling. (wintermute.com) That is a different game from exchange trading because the market is partly inside blockchain code itself. If a centralized exchange is like trading cars on a highway, decentralized finance is like trading while also reading the road rules from the asphalt in real time. (wintermute.com) The timing matters too. On February 10, 2026, Wintermute announced a London “Algorithmic Trader Assessment Day” for graduates, with Python problem-solving, market-making challenges, and trading tests, and said successful participants could move to final interviews. (wintermute.com) Put together, these listings show a firm still spending on people who can turn code into pricing, execution, and prediction. The common thread across all four jobs is not “crypto enthusiasm”; it is backtesting, microstructure, low-latency systems, and the ability to ship models into live markets where mistakes cost money immediately. (jobs.lever.co)