Distributed Computing Application Engineer

Oxford Knight; London; On-site; GBP 60,000 - 80,000; Full time

Job summary

A global quantitative investment manager in London is seeking a Distributed Computing Application Engineer to optimize workflows across locations using platforms like Ray and YellowDog. The ideal candidate will have a degree in Computer Science or Engineering, strong Python skills, and experience with cloud platforms. This is an exciting opportunity to work in a data-driven environment with a culture of innovation.

Qualifications

• Strong understanding of loosely/tightly coupled workloads.
• Experience with HPC platforms and job/resource scheduling.
• Advanced use of Ray for ML pipelines, tuning, and distributed execution.

Responsibilities

• Collaborate with business teams to integrate distributed computing into workflows.
• Optimize applications for performance on distributed platforms.
• Provide architectural and technical guidance on distributed computing design and development.

Skills

Cloud platforms (AWS, Azure, Google Cloud)

Python

Docker

Kubernetes

Analytical skills

Education

Bachelor’s degree in Computer Science, Engineering, or related field

Tools

Ray

YellowDog

Job description

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Distributed Computing Application Engineer, London

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Client:

Oxford Knight

Location:

London, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Reference:

62b412f898dd

Job Views:

22

Posted:

12.08.2025

Expiry Date:

26.09.2025

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Job Description:

My client is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. A technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped the collaborative mindset, enabling them to solve the most complex challenges. They have a culture of innovation which continuously drives their ambition to deliver high quality returns for investors.

The Workload Scheduling team is seeking a skilled Distributed Computing Application Engineer. In this role, you’ll collaborate with diverse business units to architect and optimize large-scale, compute-intensive workflows across multiple locations. Leveraging platforms such as Ray and YellowDog you’ll guide the integration and support of distributed computing solutions, driving performance and scalability in complex environments.

Responsibilities:

• Collaborate with business teams to integrate distributed computing into workflows
• Optimize applications for performance on distributed platforms
• Provide architectural and technical guidance on distributed computing design and development
• Design, implement, and manage systems using Ray and YellowDog

Requirements:

• Bachelor’s degree in Computer Science, Engineering, or related field
• Strong understanding of loosely/tightly coupled workloads
• Experience with HPC platforms and job/resource scheduling
• Proficiency with cloud platforms: AWS, Azure, or Google Cloud
• Experience with large-scale systems (1000+ nodes, 10k+ tasks)
• Advanced use of Ray for ML pipelines, tuning, and distributed execution
• Proficient in Python and Conda; skilled in Docker and Kubernetes
• Knowledge of IAM and networking (TCP/IP, UDP/IP, LAN/WAN)
• Strong analytical, independent problem-solving, and communication skills

Whilst we carefully review all applications, to all jobs, due to the high volume of applications we receive it is not possible to respond to those who have not been successful.