Machine Learning Engineer

Point72; New York (NY); On-site; USD 180,000 - 240,000; Full time

Job summary

Cubist Systematic Strategies, an affiliate of Point72, is seeking a Machine Learning Engineer for its High Frequency Trading Technology team. The role involves applying AI to solve real-world problems and building a production AI agent to monitor issues and suggest actions.

You will also assist the AI research group on projects such as synthetic data for training and MCP agents to streamline research. Strong ML background is required.

Qualifications

• PhD or PhD candidate in machine learning, computer science or related field.
• Strong background in sequential modeling and time series forecasting with deep learning.
• Experience translating mathematical models into code.
• Proficiency in Python and R, with ML libraries TensorFlow or PyTorch.
• Experience in data-driven research environments; NLP is a plus.
• Excellent analytical and communication skills; collaborative mindset.

Responsibilities

• Apply AI technologies to solve real-world problems on the High Frequency Trading Tech team.
• Develop production AI agents to monitor and suggest actions for production issues.
• Collaborate with AI research to create synthetic data and streamline research workflows.

Skills

Sequential modeling

Time series forecasting

Deep learning

Representation learning

Python

R

NLP

Analytical skills

Independent research

Communication skills

Education

PhD or PhD candidate in ML/CS

Tools

TensorFlow

PyTorch

Job description

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