Quantitative Developer, Research & ML Engineering, Systematic Macro

Overview

In this role you build and deployed ML models on high-frequency market data, and shape the research and compute infrastructure behind them. You will collaborate with the Senior Portfolio Manager to translate models into live trading signals while improving the pod’s data processing, scalability, and production readiness. You’ll enhance end-to-end ML pipelines and partner with technology teams to leverage shared platforms. This opportunity combines cutting-edge ML with systematic trading in a high-impact, data-driven environment.

Responsibilities

• Design, train and productionize large-scale ML models (classical and deep learning) on high-frequency data
• Enhance end-to-end ML pipeline: data processing, distributed computation, scalable parameter search, validation
• Improve speed, scalability, and reliability of signal development and production migration
• Collaborate with broader technology teams to utilize shared internal platforms and services

Key requirements

• Master’s or PhD/Post doctorate in Computer Science, Mathematics, Statistics, Engineering, Physics, or related quantitative field from a leading institution
• 3+ years in software engineering, quantitative development, or related computational role
• Experience building and validating ML models on large, complex datasets (classical and deep learning)
• Experience building distributed computing systems for ML applications
• Strong Python programming skills with parallelism and distributed compute; strong C++ knowledge is a plus
• Experience building data-intensive tools, research workflows, or model development infrastructure
• Strong Linux development experience
• Experience building agentic AI systems (tool use, orchestration, evaluation)
• collaborative
• entrepreneurial
• problem-solving
• Python (advanced, distributed compute, bindings with C++)
• C++ (plus)
• distributed computing for ML

Report this job