Help to lead the development and global rollout of our research framework for defining and training models through various optimization procedures (supervised learning, backtesting etc.), as well as its integration with our platform for deploying and running those models in production Partner with Quantitative Researchers to conduct research: test hypotheses and tune/develop data-driven systematic trading strategies and alpha signals
Advanced degree (Master's or PhD) in Machine Learning, Statistics, Physics, Computer Science or similar 8+ years of hands-on experience MLOps, Research Engineering, or ML Research A strong background in mathematics and statistics Strong proficiency in programming languages such as Python, with experience in libraries like numpy, pytorch, polars, pandas, and ray Demonstrated experience in designing and implementing end-to-end machine learning pipelines, including data preprocessing, model training, deployment, and monitoring Understanding of and experience with modern software development practices and tools (e.g. Agile, version control, automated testing, CI/CD, observability) Understanding of cloud platforms (e. g., AWS, Azure, GCP) and containerization technologies (e. g., Docker, Kubernetes)
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