About Cubist
Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.
Role / Responsibilities
- We are seeking a Machine Learning Engineer to join the High Frequency Trading Technology team.
- This role will apply the latest AI technologies to solve various real-world problems and streamline day-to-day operations, such as creating a production support AI agent that helps monitor production problems and suggest actions.
- This role will also work with the AI research group on various projects such as creating synthetic data for training and using MCP agents to streamline research workflow.
Requirements
- PhD or PhD candidate in machine learning, computer science or other AI related research fields
- Experience with sequential modeling and time series forecasting using deep learning
- Experience with deep neural networks and representation learning
- Prior experience working in a data driven research environment
- Experience with translating mathematical models and algorithms into code
- Proficiency in programming languages such as Python and R
- Experience with machine learning software libraries such as TensorFlow or PyTorch
- Experience implementing Agent or Context engineering is strongly preferred
- Experience with natural language processing technology is strongly preferred
- Excellent analytical skills, with strong attention to detail
- Collaborative mindset with strong independent research ability
- Strong written and verbal communication skills
- Commitment to the highest ethical standards