Quantitative Software Engineer | Research Platform

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
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• Developing platform services across job scheduling, workflow orchestration, cluster management, and data processing
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• Designing and improving compute and data platforms used by researchers globally
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• Building reliable, high-performance systems in Python and Rust
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• Working on infrastructure that accelerates simulation, experimentation, and model development
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• 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
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• Experience building distributed systems or large-scale infrastructure platforms
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• Expert-level Python development experience
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• Ability to lead projects and take ownership from architecture through deployment
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• Interest in solving complex problems at the intersection of infrastructure and research enablement
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• 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
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• Ownership of critical infrastructure supporting large-scale simulations and model development
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• Collaborative environment working alongside world-class researchers, traders, and engineers
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• Opportunity to influence technical direction and platform architecture
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