Job Description
Basic Qualifications Master's or Ph.D. degree in Computer Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics, Finance, or a related field, or equivalent practical experience. At least 5 years of professional experience developing AI or quantitative trading systems using Python. Strong expertise in machine learning, deep learning, statistical modeling, and time-series forecasting . Proficiency in Python and common data science libraries such as NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow, or JAX . Experience working with large-scale financial or market datasets. Preferred Qualifications 2+ years of experience leading AI or quantitative research initiatives. Experience developing systematic trading strategies , alpha models, or portfolio optimization frameworks. Strong understanding of financial markets , including equities, futures, options, cryptocurrencies, or FX. Experience with high-frequency trading (HFT) , market microstructure, or execution algorithms is a plus. Familiarity with LLMs, reinforcement learning, or AI agents for financial applications. Experience with backtesting frameworks, factor research, and quantitative risk management. Publications in leading AI or quantitative finance conferences/journals (e.g., NeurIPS, ICML, ICLR, KDD, AAAI, Quantitative Finance ) or contributions to well-known open-source projects are preferred. Technical Skills Python (5+ years) PyTorch / TensorFlow / JAX SQL Linux Git Docker CUDA (preferred) AWS / GCP / Azure (preferred) Experience with distributed computing (Ray, Spark, Dask, etc.) Nice to Have Experience in cryptocurrency quantitative trading. Experience with market making, statistical arbitrage, or CTA strategies. Familiarity with reinforcement learning, transformers, diffusion models, or AI-driven trading agents. Experience deploying AI models into live trading environments with low latency and high reliability.
