Cubist Systematic Strategies is looking for a Machine Learning Engineer to apply AI technologies to solve real-world problems and streamline operations within their High Frequency Trading Technology team, including creating a production support AI agent and assisting the AI research group with projects like synthetic data generation and workflow streamlining.
Requirements
- Experience with sequential modeling and time series forecasting using deep learning
- Experience with deep neural networks and representation learning
- 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
Responsibilities
- 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.
- work with the AI research group on various projects such as creating synthetic data for training and using MCP agents to streamline research workflow.
Other
- PhD or PhD candidate in machine learning, computer science or other AI related research fields
- Prior experience working in a data driven research environment
- Excellent analytical skills, with strong attention to detail
- Collaborative mindset with strong independent research ability
- Strong written and verbal communication skills
