Application Engineer - Distributed Computing

JR United Kingdom; London; On-site; GBP 50,000 - 80,000; Full time

Job summary

A leading systematic hedge fund in London is seeking a Distributed Computing Application Engineer to enhance large-scale workflows. The role involves working with advanced platforms like Ray and YellowDog, providing technical leadership, and optimising applications across distributed computing environments.

Qualifications

• Bachelor's degree in a related field required.
• Hands-on experience with large-scale systems and cloud platforms.
• Strong programming skills in Python and experience with container orchestration.

Responsibilities

• Partner with teams to integrate distributed computing into workflows.
• Optimise applications for performance on distributed systems.
• Design and manage distributed computing solutions using Ray and YellowDog.

Skills

Cloud platforms (AWS, Azure, GCP)

Programming in Python

Experience with HPC

Containerisation with Docker and Kubernetes

Education

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

Tools

Ray

YellowDog

Job description

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Application Engineer - Distributed Computing, london

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Client:

Selby Jennings

Location:

london, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Views:

3

Posted:

10.06.2025

Expiry Date:

25.07.2025

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Job Description:

Distributed Computing Application Engineer - Systematic Hedge Fund - London

Our client, a leading systematic hedge fund, is seeking a Distributed Computing Application Engineer to join their London-based team. This role involves collaborating across multiple business units to architect and optimise large-scale, compute-intensive work flows spanning global locations.

You will work with cutting-edge platforms such as Ray and YellowDog, driving the integration and support of distributed computing solutions to enhance performance and scalability in complex environments.

Key Responsibilities:

• Partner with business teams to embed distributed computing into core workflows.
• Optimise applications for high performance on distributed platforms.
• Provide architectural and technical leadership in the design and development of distributed systems.
• Design, implement, and manage distributed computing solutions using Ray and YellowDog.

Required Skills & Experience:

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Deep understanding of loosely and tightly coupled workloads.
• Hands-on experience with HPC platforms and job/resource scheduling.
• Proficiency in cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
• Proven experience working with large-scale systems (1000+ nodes, 10,000+ tasks).
• Advanced expertise in Ray for machine learning pipelines, hyperparameter tuning, and distributed execution.
• Strong programming skills in Python and experience with Conda.
• Proficiency with Docker and Kubernetes for containerisation and orchestration.