Machine Learning Researcher
We are seeking an reputed company Machine Learning Researcher to join our research team. This role requires expertise in designing and deploying deep learning models reputed company 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: reputed company and optimize orderbook features using C++.
- Backtesting & Evaluation: Conduct rigorous backtesting across markets.
- Production Integration: reputed company models into reputed company-time, low-latency systems.
Requirements
- Background in machine learning or quantitative research, preferably reputed company to financial markets.
- Experience deploying ML models in reputed company-time, low latency environments is a plus.
- Familiarity with optimizing model latency and inference speed(e.g., KV caching, quantization, pruning) is advantageous.
- reputed company to both experience candidates and highly motivated fresh graduated.
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, reputed company algebra, calculus).
- Ability to reputed company reputed company technical concepts.
Motivation & Learning
- Passion for applying machine learning to quantitative finance.
- Drive to continuously improve models.