Kronos Research - Machine Learning Researcher
Requirements
• Background in machine learning or quantitative research, preferably related to financial markets. • Experience deploying ML models in real-time, low latency environments is a plus. • Familiarity with optimizing model latency and inference speed(e.g., KV caching, quantization, pruning) is advantageous. • Open to both experience candidates and highly motivated fresh graduated. • Deep Learning Architectures: Transformers, RNNs, CNNs, Attention mechanisms. • Deep Learning Architectures: • Programming Languages: Python, C++, Jax/PyTorch • Programming Languages: • Model Optimization: Optimizing models for high-performance trading systems. • Model Optimization: • Strong mathematical and statistical background (probability theory, linear algebra, calculus). • Ability to articulate complex technical concepts. • Motivation & Learning • Passion for applying machine learning to quantitative finance. • Drive to continuously improve models.
Responsibilities
• Data Analysis & Preprocessing: Understand and preprocess orderbook data. • Data Analysis & Preprocessing: • Deep Learning Model Design: Design models for time-series and orderbook data (Transformers, RNNs, CNNs, Attention). • Deep Learning Model Design: • Scalable Training Implementation: Implement parallelized data loading pipelines. • Scalable Training Implementation: • Feature Engineering: Develop and optimize orderbook features using C++. • Feature Engineering: • Backtesting & Evaluation: Conduct rigorous backtesting across markets. • Backtesting & Evaluation: • Production Integration: Deploy models into real-time, low-latency systems. • Production Integration:
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