Distributed Compute Engineer: Optimize Research Workloads

Wehrtyou; New York (NY); On-site; USD 200,000 - 300,000; Full time

Job summary

Hudson River Trading (HRT) is seeking a distributed compute engineer to help make our research environment fast and reliable. You will work with quantitative traders and software engineers to optimize the stack from user workloads to low-level performance.

Responsibilities include maintaining resource scheduling, data caching, and job monitoring; improving iteration speed; tuning at the infra level; and sharing metrics with users while shaping the platform's technical direction.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or a related field.
• Strong C++ expertise (daily use preferred).
• Python familiarity preferred.
• Experience collaborating closely with quantitative researchers and traders to understand their needs.
• Great communication capabilities.
• Superior design, debugging, and problem solving skills.
• Knowledge of UNIX operating systems (Linux), system/processor performance, and network communication.

Responsibilities

• Maintain and improve resource scheduling, data caching, and job monitoring to make research as easy, fast, and efficient as possible, using both in-house and open source solutions.
• Optimize workloads at the user level to speed up user iteration speed.
• Tune workloads at the infrastructure level to make them more resource-efficient.
• Share metrics and real-time information with users to give insight into workload behavior.
• Sit down with users to understand their specific technical needs.
• Contribute individually and through leadership and coordination of the above.
• Set technical direction for the platform and take holistic ownership of the software infrastructure that supports Algo research.

Skills

C++ expertise

Python familiarity

Communication

Linux/UNIX knowledge

Performance tuning

Education

Bachelor's degree in Computer Science/Engineering

Job description

Hudson River Trading (HRT) is seeking a distributed compute engineer to help make our research environment fast and reliable. You will work with quantitative traders and software engineers to optimize the stack from user workloads to low-level performance.

Responsibilities include maintaining resource scheduling, data caching, and job monitoring; improving iteration speed; tuning at the infra level; and sharing metrics with users while shaping the platform's technical direction.