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Machine Learning Researcher
- New York, New York, United States
- New York, New York, United States
Ăśber
We are seeking an experienced Machine Learning Researcher to join our research team. This role requires expertise in designing and deploying deep learning models within high-performance, low-latency trading systems. You will be working on developing robust, scalable models and integrating them into our trading infrastructure. Responsibilities
Data Analysis & Preprocessing: Understand and preprocess orderbook data. Deep Learning Model Design: Design models for time-series and orderbook data (Transformers, RNNs, CNNs, Attention). Scalable Training Implementation: Implement parallelized data loading pipelines. Feature Engineering: Develop and optimize orderbook features using C++. Backtesting & Evaluation: Conduct rigorous backtesting across markets. Production Integration: Deploy models into real-time, low-latency systems. 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 experienced candidates and highly motivated fresh graduates. Technical Skills
Deep Learning Architectures: Transformers, RNNs, CNNs, Attention mechanisms. Programming Languages: Python, C++, Jax/PyTorch Model Optimization: Optimizing models for high-performance trading systems. Analytical & Communication Skills
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.
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Sprachkenntnisse
- English
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