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Top-tier systematic trading firm hiring an ML researcher to push the firm's alpha research beyond classical statistical methods. Compensation Base: $400K Total Comp: $1M-2M Structure: Base + Sign-on Bonus + P&L attachment + performance bonus Role Description Design, train, and deploy ML models (deep learning, NLP, reinforcement learning, or large-scale ensemble methods) for alpha generation across equities, futures, and other liquid markets Own the full pipeline from research and backtesting to live production deployment Mine large, noisy, non-stationary financial datasets to engineer features and signals that hold up out-of-sample Collaborate with quant researchers, engineers, and traders to integrate ML-driven signals into existing systematic strategies Ideal Candidate 2 to 5 years of experience applying machine learning in a quantitative research, trading, or comparable high-stakes production environment Strong foundations in statistics, applied ML, and time-series/panel data methods; healthy skepticism about overfitting in noisy financial data Proficiency in Python; experience with large-scale data pipelines and model deployment infrastructure PhD or 2 years of industry experience in ML, statistics, CS, or a related quantitative field a strong plus Will wait up to 12 months non-compete.