Senior AI Compute & Data Infrastructure Architect

CDFAM - Computational Design Symposium; Palo Alto, Northern (CA, KY); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Vinci is hiring a senior infrastructure engineer in Palo Alto to own the compute and data architecture for large-scale physics training workloads. You will ensure scalable GPU capacity, efficient scheduling, and robust data pipelines to feed petabyte-scale datasets for AI research.

You will lead hands-on engineering, mentor new engineers, and set technical direction with the AI team and leadership. This role emphasizes reliability, cost control, and scalable experimentation.

Qualifications

• 10+ years building large-scale distributed systems.
• Direct experience with multi-node training on GPUs.
• Experience serving petabyte-scale training data.
• Ability to set scheduling and quota policies for GPUs.
• Track record mentoring engineers and teaching across teams.
• Ability to define technical direction and roadmaps.

Responsibilities

• Define compute architecture for scalable GPU capacity.
• Own workload scheduling across training and validation.
• Design data infra to feed training jobs at scale.
• Build and operate training/validation platform.
• Ensure reliability, utilization, and cost targets.
• Contribute production code and perform reviews.
• Mentor team members and help grow the org.
• Set long-term technical direction with leadership.

Skills

Distributed systems

GPU infrastructure

Multi-node training

Scheduling & quotas

Mentoring engineers

Technical direction

Cost optimization

Education

Advanced degree

Tools

Kubernetes

Ray

Slurm

Airflow

Job description

Vinci is hiring a senior infrastructure engineer in Palo Alto to own the compute and data architecture for large-scale physics training workloads. You will ensure scalable GPU capacity, efficient scheduling, and robust data pipelines to feed petabyte-scale datasets for AI research.

You will lead hands-on engineering, mentor new engineers, and set technical direction with the AI team and leadership. This role emphasizes reliability, cost control, and scalable experimentation.