

Responsibilities:
Design, develop, train, and optimize AI and Machine Learning models.
Improve model performance for trading signal generation.
Evaluate, validate, and enhance prediction accuracy.
Deploy and maintain models in production environments.
Collaborate with Quant Researchers and Data Analysts to develop intelligent trading systems.
Requirements:
Strong expertise in designing, training, and optimizing Neural Networks.
Experience with Ensemble Learning methods such as Random Forest, Gradient Boosting, XGBoost, and Stacking.
Strong understanding of Time Series and Sequential Data Modeling.
Experience with recurrent neural networks including RNN, LSTM, and GRU.
Familiarity with Reinforcement Learning concepts and algorithms.
Proficiency in Python.
Hands-on experience with PyTorch or TensorFlow.
Solid knowledge of Machine Learning and Deep Learning algorithms.
Experience with Scikit-learn and MLOps practices.
Experience deploying models and working with APIs.
Experience applying AI in financial markets is a strong plus.
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