Quantitative Software Engineer | Research Platform
Technology
Job Description
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.
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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.
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What you'll work on:
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- 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
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What they're looking for:
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- 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
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Why this opportunity stands out:
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- 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
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