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Selby Jennings
ML Researcher/Engineer
Selby Jennings
New York•Hybrid•Salary•3-6 Yrs•1 day ago
Job description
Hybrid
Overview
Machine Learning Engineer (Research-Focused) - Equities Trading
Responsibilities
- Research, prototype, and productionize ML/statistical models for alpha signals, market microstructure, and execution strategies in equities.
- Partner with quantitative researchers and traders to translate research ideas into robust, low-latency production systems.
- Build and maintain scalable data pipelines, feature stores, and backtesting frameworks for large-scale market and alternative data.
- Explore modern ML techniques (deep learning, reinforcement learning, time-series modeling, NLP on alt-data) and evaluate their applicability to trading problems.
- Own the full model lifecycle: research → backtest → deployment → monitoring → iteration.
- Contribute to internal research infrastructure and tooling that accelerates the broader quant/ML team.
Qualifications
- Bachelor's, Master's, or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Physics, or a related quantitative field.
- 3+ years of experience building and deploying ML models in a research-driven or production environment (trading, big tech, or top-tier research labs).
- Strong proficiency in Python (NumPy, pandas, PyTorch/TensorFlow, scikit-learn); working knowledge of C++ is a strong plus.
- Solid foundation in statistics, probability, time-series analysis, and modern ML methods.
- Strong software engineering fundamentals
- Exposure to low-latency systems, distributed computing, or GPU-accelerated workflows
- Publications or open-source contributions in ML or quantitative finance