Quant Systems: Systems Developer (New York) (4295F7B)

Referment; New York (NY); On-site; USD 90,000 - 130,000; Full time

Job summary

Referment is seeking an experienced systems engineer to design and improve workload scheduling, fleet management, and clustered file-system operations for large-scale compute environments. You will also tune kernel and network performance while building tools to analyze infrastructure behavior for trading and research workloads.

The role requires strong programming skills in Python, Go, or Rust, and a Computer Science degree or up to five years of applicable experience.

Qualifications

• Candidates must have strong programming ability in Python, Go, Rust, or a similar language.
• A computer science degree or up to five years of comparable practical experience is required.

Responsibilities

• Design workload scheduling, fleet management, and clustered file-system operations for large-scale compute environments.
• Tune kernel and network performance while building tools to analyze infrastructure behavior for trading and research workloads.

Skills

Python

Go

Rust

Linux

Networking

HPC

Storage

GPU Infrastructure

Data-centre Hardware

Workload Scheduling

Fleet Management

Clustered File Systems

Kernel Tuning

Performance Tuning

Distributed Computing

Software Engineering

Education

Computer Science degree or equivalent experience

Job description

The role involves designing and improving workload scheduling, fleet management, and clustered file-system operations for large-scale compute environments. You will also tune kernel and network performance while building tools to analyze infrastructure behavior for trading and research workloads.

Requirements: Candidates must have strong programming ability in Python, Go, Rust, or a similar language. A computer science degree or up to five years of comparable practical experience is required.

Key Skills: Python, Go, Rust, Linux, Networking, HPC, Storage, GPU Infrastructure, Data-centre Hardware, Workload Scheduling, Fleet Management, Clustered File Systems, Kernel Tuning, Performance Tuning, Distributed Computing, Software Engineering