Distributed Compute Tech Lead

An elite high frequency trading firm is seeking a Distributed Compute Tech Lead to design and operate large-scale computing systems that powers quantitative research. This role focuses on improving research efficiency by building robust infrastructure, APIs, and libraries that abstract complexity and enable researchers to innovate faster. You will serve as a bridge across disciplines, collaborating with researchers, engineers, and leadership to shape technology direction and strategy for the firm's research platform.

• Architect and operate distributed or high-performance computing systems at scale, ensuring reliability, scalability, and performance.
• Design and implement APIs and libraries that abstract infrastructure complexity, making compute resources easily accessible to researchers.
• Optimize job scheduling and resource allocation using tools like SLURM and other HPC schedulers.
• Collaborate with researchers to identify bottlenecks and deliver solutions that accelerate research workflows.
• Partner with leadership and cross-functional teams to define technology strategy and influence long-term direction.
• Develop automation and orchestration tools for compute-intensive tasks.
• Establish best practices for distributed computing and mentor team members on HPC resource management.

• Bachelor's degree in computer science or equivalent
• Minimum of 5 years of experience in architecting Distributed or High Performance Computing systems, and designing and scaling research clusters.
• Strong expertise in Python for building tools, automation, and APIs.
• Familiarity with C++ for performance-critical components.
• Extensive experience with job schedulers (e.g., SLURM) and distributed computing frameworks.
• Proven experience architecting and operating distributed or HPC systems at scale.
• Strong background in building developer-facing APIs or libraries that abstract infrastructure.
• Ability to collaborate across disciplines and influence technology strategy.
• Excellent problem-solving skills and ability to thrive in a fast-paced, high-performance environment.

• Experience in financial services or high-frequency trading environments.
• Knowledge of containerization (Docker, Kubernetes) and cloud/HPC hybrid setups.
• Familiarity with performance profiling and tuning for large-scale systems.