Distributed Computing Application Engineer- Systematic Quant Fund

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

Job summary

A global investment management firm in London is seeking a Distributed Computing Application Engineer to collaborate with various business units to optimize large-scale workflows. Candidates should have a degree in Computer Science and experience with cloud platforms like AWS, Azure, or Google Cloud. This role requires strong skills in distributed systems, Python, Docker, and Kubernetes.

Qualifications

• Strong understanding of loosely/tightly coupled workloads.
• Experience with large-scale systems (1000+ nodes, 10k+ tasks).
• Strong analytical, independent problem-solving, and communication skills.

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, or Google Cloud

Python

Docker

Kubernetes

Monitoring/troubleshooting distributed environments

Education

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

Tools

Ray

YellowDog

HPC platforms

Job description

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.

About the role

• 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)
• Expertise in monitoring/troubleshooting distributed environments
• 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.

Contact
If this sounds like you, or you'd like more information, please get in touch:

George Hutchinson-Binks
[e-mail]
([phone]
linkedin.com/in/george-hutchinson-binks-a62a69252