Research Technology Engineer - Lead...

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THE COMPANY
Our client is a leading algorithmic trading company partnering with counterparties, exchanges, and e-trading venues globally to provide liquidity in the Equity, FX, Fixed Income, Commodity, and Futures markets. They provide consistent liquidity, helping market participants around the world obtain the best prices across the asset classes they cover, regardless of changing market conditions.

Technology is at the core of their business, and they attract outstanding talent from diverse industry backgrounds. The company fosters a collaborative and respectful environment where teamwork and excellence drive everything they do. Their non-hierarchical culture values every individual’s contributions, creating an atmosphere where innovation and performance thrive.

THE ROLE
Our client operates one of the largest high-performance computing (HPC) clusters in the world, developed by their research technology team through custom-built software. They’re not afraid to create their own filesystems, job distribution engines, orchestration tools, and build systems when it offers the optimal approach to managing infrastructure at scale.

They are looking for a senior-level engineer to join their experienced team, helping to design their datacenters, select the right hardware, tune operating systems, storage, and networks, manage orchestration and observability, and write the software that ensures fair and efficient distribution of work on their compute cluster. This full-stack team works closely with researchers to build the most performant, reliable, and transparent system possible.

The infrastructure they maintain enables the company to trade globally, with daily volumes exceeding $250bn across a wide range of asset classes.

RESPONSIBILITIES
The ideal candidate will:
  • Contribute to all components of the HPC infrastructure and code, and support the growth of one of the biggest private compute clusters worldwide.
  • Develop software that runs on a continually expanding compute cluster, currently featuring ~1PB memory, ~110K CPU cores, >25,000 GPUs, and 200+PB of mixed SSD and HDD storage connected by a high-performance network.
  • Thrive in an environment where improvements can often be made rapidly, and where the impact of those changes is immediately visible, directly enhancing the quantitative research function.
    • Examples of current projects include:
  • Implementing a custom-built filesystem
  • Enhancing host monitoring infrastructure
  • Bare metal provisioning
  • Migrating to a new lightweight, high-performance metrics visualization system
    • ESSENTIAL ATTRIBUTES
  • 5–10 years of direct experience with large-scale compute infrastructure; financial services experience is not required.
  • Strong programming skills, preferably with recent exposure to Python and at least one statically typed language.
  • A strong academic background in STEM and/or exceptional technical credentials with a drive for excellence.
  • Clear working knowledge and hands-on experience with computer networks, including design, configuration, monitoring, automation, and an understanding of underlying hardware, IP/Ethernet, and InfiniBand.
  • Proficiency in managing large-scale infrastructure using code for hardware performance evaluation, automated builds, patching, application deployment, observability, and storage.
  • A desire to solve complex problems from the ground up, not just through pre-existing components.
  • The ability to apply knowledge across many layers of the technology stack (network, hardware, OS, software) to achieve optimal results.
  • Familiarity with large-scale distributed systems.
  • Understanding of machine learning frameworks and compute offload devices like GPUs is a plus.
    • Skip the line...
    If you have read this far and you believe you are in the top 1% of your field of expertise, then please reach out to me directly with your resume and a brief note outlining your suitability for this role. shane@cryptorecruit.com
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    Location:
    London
    Job Type:
    FullTime