HPC Research Platform - Software Engineer

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 our 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

We are seeking a Software Engineer to join our HPC Research Infrastructure team, responsible for building and evolving an in-house research platform that underpins quantitative research across the firm. The platform provides scalable, secure, and efficient access to high-performance compute and data, enabling researchers to run large-scale, compute-intensive pipelines with minimal friction. 

In this role, you will design and implement core platform components including APIs, backend services, and tooling to support job submission, scheduling, resource management, security, and observability across heterogeneous compute environments (on-prem and/or cloud). You will operate at the intersection of software engineering, distributed systems, and infrastructure, helping to deliver a robust, developer-friendly platform that enables research at scale and has company-wide impact. 

Responsibilities

• Collaborate closely with quantitative researchers, platform engineers, and other cross-functional teams to understand research workflows and translate them into scalable, reliable platform capabilities 
• Design, build, and maintain distributed services and APIs that manage compute workloads, data access, and execution lifecycles across HPC environments 
• Improve the usability, reliability, and performance of large-scale quantitative research workflows, with a strong focus on developer experience and operational excellence 
• Contribute to the design and implementation of scheduling, security, and observability solutions suitable for highly parallel, compute-heavy systems 
• Work with state-of-the-art infrastructure and modern software engineering practices to support massive compute pipelines and rapidly evolving research demands 
• Take ownership of complex technical problems, operating with a high degree of autonomy while making pragmatic trade-offs to deliver impact quickly and safely 

Your Present Skillset 

• BSc / MEng / PhD in Computer Science or a closely related field, or equivalent practical experience, with 5+ years of professional software development 
• Strong proficiency in at least one statically-typed programming language (e.g. C, C++, Java, Rust), with an interest in Go (prior experience welcome but not required). Experience with Python is a plus 
• Required: 5+ years of experience designing, implementing, and operating large-scale distributed systems in production environments 
• Preferred: Prior experience in quantitative finance or working closely with quantitative researchers and data-intensive workloads 
• Preferred Understanding of GPU programming models and performance considerations (e.g. CUDA, memory hierarchies, parallel execution), with exposure to ML frameworks such as PyTorch or TensorFlow 
• Solid understanding of systems concepts such as concurrency, performance, fault tolerance, and reliability 
• Comfortable working in fast-moving, rapidly evolving environments; proactive in learning new technologies and improving existing systems 
• Pragmatic engineering mindset, with a focus on delivering high-impact solutions while maintaining long-term platform health 

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.