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:
1. Collaborate with business teams to integrate distributed computing into workflows
2. Optimize applications for performance on distributed platforms
3. Provide architectural and technical guidance on distributed computing design and development
4. Design, implement, and manage systems using Ray and YellowDog
Requirements:
5. Bachelor’s degree in Computer Science, Engineering, or related field
6. Strong understanding of loosely/tightly coupled workloads
7. Experience with HPC platforms and job/resource scheduling
8. Proficiency with cloud platforms: AWS, Azure, or Google Cloud
9. Experience with large-scale systems (1000+ nodes, 10k+ tasks)
10. Expertise in monitoring/troubleshooting distributed environments
11. Advanced use of Ray for ML pipelines, tuning, and distributed execution
12. Proficient in Python and Conda; skilled in Docker and Kubernetes
13. Knowledge of IAM and networking (TCP/IP, UDP/IP, LAN/WAN)
14. 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.