Machine Learning Engineer

Who you are

You are a PhD or PhD candidate in machine learning, computer science, or other AI-related research fields, with a strong foundation in sequential modeling and time series forecasting using deep learning. Your experience includes working with deep neural networks and representation learning, and you have a proven track record in a data-driven research environment. You excel at translating mathematical models and algorithms into code, demonstrating proficiency in programming languages such as Python and R. Your familiarity with machine learning software libraries like TensorFlow and PyTorch is essential, and you have experience implementing agent or context engineering, as well as natural language processing technology. You possess excellent analytical skills, a collaborative mindset, and strong written and verbal communication skills, all while maintaining a commitment to the highest ethical standards.

What you'll do

In this role, you will join the High Frequency Trading Technology team at Cubist Systematic Strategies, an affiliate of Point72. Your primary responsibility will be to apply the latest AI technologies to solve various real-world problems and streamline day-to-day operations. This includes creating a production support AI agent that helps monitor production problems and suggests actions. You will collaborate closely with the AI research group on projects such as creating synthetic data for training and utilizing MCP agents to enhance research workflows. Your work will directly impact the efficiency and effectiveness of trading strategies across multiple liquid asset classes, including equities, futures, and foreign exchange.

What we offer

At Point72, you will be part of a dynamic team that values rigorous research and innovative solutions. We provide a collaborative environment where your contributions will be recognized and rewarded. You will have access to unparalleled data sources and the opportunity to work on cutting-edge AI technologies that drive our trading strategies. We encourage you to apply even if your experience doesn't match every requirement, as we value diverse perspectives and backgrounds.