Machine Learning Engineer

Role Overview

Graham Capital Management seeks a Machine Learning Engineer to join its Data Science team, supporting quantitative research and discretionary trading with ML models and data pipelines. The role involves collaborating with researchers, portfolio managers, and operations to build and deploy machine learning solutions for financial markets.

Responsibilities

• Work with quantitative researchers, portfolio managers, and technology teams to identify data-driven opportunities.
• Develop time-series and forecasting models using large, unstructured datasets.
• Apply state-of-the-art machine learning and statistical methods to generate insights for trading strategies.
• Build, test, and deploy production-ready models and services in containerized environments.
• Communicate findings to technical and non-technical stakeholders.

Requirements

• Undergraduate or higher degree in Computer Science, Engineering, Operations Research, or other quantitative discipline
• 3+ years of hands-on experience with Machine Learning and Statistics on large, unstructured, data sets
• Experience writing production code for multi-client systems serving model results is a great plus
• Ability to clearly communicate research findings to technical and nontechnical stakeholders
• Full-stack experience with Python (preferred) or C++, Spark/Scala, SQL or other distributed data processing technologies as well as experience working comfortably building and deploying services and models in containerized environments
• Experience with scientific computing, statistics, optimization, time series, panel data, etc.
• Comfortable handling multiple projects to solve varied problems working with multiple teams
• Detail-oriented mindset
• Sense of ownership of his/her work, working well both independently as well as collaboratively