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Machine Learning Engineer

Job in New York, New York County, New York, 10261, USA
Listing for: Point72
Full Time position
Listed on 2026-07-18
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, Data Scientist, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 180000 - 240000 USD Yearly USD 180000.00 240000.00 YEAR
Job Description & How to Apply Below
Location: New York

About Cubist

Cubist Systematic Strategies, an affiliate of Point
72, 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 Tensor Flow or Py Torch
  • 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
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