Platinum & Partners is retained by a top-tier global hedge fund to identify an Applied ML Engineer for a newly formed systematic equities pod deploying intraday mean reversion and microstructure strategies. This is a hands-on engineering role at the sharp end of live alpha generation — you will be developing, optimising and deploying machine learning models that feed directly into production trading signals.
The focus is tree-based ensemble methods applied to high-frequency financial data, working closely with the Portfolio Manager and quantitative researchers to turn ML models into live trading output. The firm wants someone who can start as soon as possible.
THE ROLE
- Develop and optimise tree-based ensemble models — LightGBM, XGBoost, CatBoost — for intraday alpha prediction
- Design and implement end-to-end ML pipelines: feature engineering, training, validation, deployment and monitoring
- Build robust cross-validation frameworks adapted to financial time-series — purged k-fold, walk-forward and similar
- Engineer features from market microstructure data: order flow imbalance, spread dynamics, volume patterns and cross-asset signals
- Implement model explainability tools — SHAP, feature importance — to understand and validate signal sources
- Optimise model inference for low-latency production deployment
- Monitor model performance in production: detect drift, staleness and regime changes
- Collaborate with the C++ developer to integrate ML predictions into the real-time trading engine
- Experiment with TabPFN and other rapid-prototyping tools for fast signal discovery
WHAT THEY ARE LOOKING FOR
- Master's degree in Computer Science, Statistics, Mathematics, Machine Learning or a related quantitative field
- 3+ years of experience building and deploying ML models in a production environment — finance experience preferred
- Deep expertise in tree-based ensemble methods: LightGBM, XGBoost, CatBoost — including hyperparameter tuning, regularisation and feature selection
- Strong Python: scikit-learn, Polars/Pandas, NumPy
- Strong understanding of overfitting, data leakage and proper evaluation methodology for financial time-series
- Ability to explain model behaviour clearly to non-ML stakeholders — communication matters here
- Familiarity with AI-assisted development tools is a plus
- Experience with financial market data — tick data, order book, corporate actions — and knowledge of market microstructure and intraday trading dynamics are both meaningful advantages
WHY THIS ROLE
- A top-tier global hedge fund with the data infrastructure, capital and intellectual environment to work on genuinely hard ML problems
- Newly formed pod — you are building something from the ground up, not maintaining someone else's legacy system
- Direct collaboration with the Portfolio Manager and researchers — your models go straight into live trading, not into a report
- Intraday mean reversion and microstructure strategies are among the most technically demanding areas of systematic equities — this is frontier work
- Base $150,000–$200,000 with a discretionary performance bonus reflecting the firm's Tier 1 position — total compensation is significantly above the base range
- New York City — embedded in the team whose performance depends on what you build
ABOUT PLATINUM & PARTNERS
Platinum & Partners is the specialist quant and systematic executive search firm. Retained and exclusive mandates only. All candidate conversations handled in complete confidence.