Machine Learning Researcher/Engineer

Role Overview

Join our team in New York, NY as a Machine Learning Researcher/Engineer where you'll be driving the research, prototyping, and deployment of machine learning and statistical models aimed at alpha signal generation, market microstructure, and execution strategies within equities trading.

Primary Responsibilities

• Develop and move ML/statistical models from concept through to production for equity market applications involving alpha signals and execution methods.
• Collaborate closely with quantitative research teams and traders to convert research insights into operational, low-latency systems.
• Design and maintain extensive data infrastructure including scalable pipelines, feature storage, and backtesting platforms utilizing large-scale market and alternative datasets.
• Investigate and apply advanced machine learning methods such as deep learning, reinforcement learning, time-series techniques, and natural language processing on alternative data to address trading challenges.
• Manage the complete lifecycle of models: from research and backtesting to deployment, ongoing monitoring, and iterative refinement.

Required Qualifications and Skills

• Degree qualifications at Bachelor's level or higher in Computer Science, Machine Learning, Statistics, Mathematics, Physics, or a closely related quantitative discipline.
• At least three years of experience developing and operationalizing machine learning models in research-driven or production settings, ideally in trading environments, leading technology firms, or prestigious research institutions.
• Proficiency in Python programming with expertise in libraries such as NumPy, pandas, PyTorch or TensorFlow, and scikit-learn; familiarity with C++ is considered a valuable addition.
• Strong background in statistics, probability theory, time-series analysis, and current machine learning methodologies.
• Experience handling large and noisy datasets alongside constructing reproducible research pipelines.
• Robust software engineering practices including writing clean, testable code, version control, and system design skills.