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
