Quantitative Software Engineer | Research Platform (Chicago)

I've partnered with a leading quantitative trading firm to scale their research platform team that powers large-scale simulations, model training, and data-driven decision-making across the business.

This team sits at the intersection of distributed systems, high-performance computing, and quantitative research, owning the infrastructure and software that enables researchers and traders to rapidly test ideas and generate insights from massive datasets.

What you'll work on:

• Building and scaling distributed systems that support large-scale computational workloads
• Developing platform services across job scheduling, workflow orchestration, cluster management, and data processing
• Designing and improving compute and data platforms used by researchers globally
• Building reliable, high-performance systems in Python and Rust
• Working on infrastructure that accelerates simulation, experimentation, and model development
• Partnering directly with researchers, traders, and engineers to solve complex technical challenges

What they're looking for:

• Strong software engineering fundamentals and systems design experience
• Experience building distributed systems or large-scale infrastructure platforms
• Expert-level Python development experience
• Ability to lead projects and take ownership from architecture through deployment
• Interest in solving complex problems at the intersection of infrastructure and research enablement
• Experience with Rust, C++, high-performance computing, GPUs, or CUDA is a plus

Why this opportunity stands out:

• Direct impact on the tools and platforms used to drive quantitative research and trading decisions
• Ownership of critical infrastructure supporting large-scale simulations and model development
• Collaborative environment working alongside world-class researchers, traders, and engineers
• Opportunity to influence technical direction and platform architecture