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An established industry player is seeking a Senior Engineer to join their innovative infrastructure team. This role focuses on developing and maintaining cutting-edge high-performance storage systems that support advanced research and trading operations. You will leverage your extensive experience in storage systems and Linux-based workloads to optimize infrastructure for AI/ML modelling. The collaborative culture at this forward-thinking firm encourages you to stay ahead of industry trends, providing strategic insights to enhance operations. If you thrive in a dynamic environment and are passionate about technology, this opportunity is perfect for you.
Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.
Your future role within QRT:
The successful candidate will join the infrastructure team at QRT as a Senior Engineer within our Research infrastructure engineering team. This team is responsible for our cutting-edge high-performance trading and research infrastructure and are responsible for development and maintenance across operating system platforms, software development tooling, high-performance computing, high performance networking, and large-scale storage systems.
The candidate will work directly with our research and trading teams with a primary focus on high performance storage systems supporting our high-performance computing (HPC) domain. You will already have a strong technical background in building, testing and supporting Linux based, large-scale, high-performance workloads, with likely deep exposure in technologies and vendors such as NFS, S3, CEPH, GPFS, Lustre, ROCE, VAST, WEKA or DDN.
You will work directly with our researchers to understand their technology ecosystem which is using the latest AI/ML modelling technologies. You will have had exposure to AI/ML modelling toolsets and translated these requirements into a high performance and scalable storage infrastructure.
Your present skillsets:
QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.