Application Engineer - Distributed Computing

JR United Kingdom; City Of London; On-site; GBP 60,000 - 90,000; Full time

Job summary

A leading systematic hedge fund is seeking a Distributed Computing Application Engineer in London. This role involves architecting and optimizing large-scale workflows using advanced platforms such as Ray and YellowDog. Candidates must have a strong programming background, experience with HPC platforms, and proficiency in cloud technologies.

Qualifications

• Deep understanding of loosely and tightly coupled workloads.
• Advanced expertise in Ray for machine learning and distributed execution.
• Strong experience with cloud platforms (AWS, Azure, GCP).

Responsibilities

• Partner with business teams to embed distributed computing into workflows.
• Optimize applications for high performance on distributed platforms.
• Provide leadership in designing and developing distributed systems.

Skills

Programming in Python

Proficiency in Docker

Proficiency in Kubernetes

Understanding of cloud platforms

Experience with HPC platforms

Architectural leadership

Experience with systems over 1000 nodes

Education

Bachelor's degree in Computer Science

Bachelor's degree in Engineering

Bachelor's degree in related field

Job description

Social network you want to login/join with:

Application Engineer - Distributed Computing, london (city of london)

col-narrow-left

Client:

Selby Jennings

Location:

london (city of london), United Kingdom

Job Category:

Other

-

EU work permit required:

Yes

col-narrow-right

Job Views:

3

Posted:

10.06.2025

Expiry Date:

25.07.2025

col-wide

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.