Remote-friendly GPU ML Systems Engineer — Scheduler & Infra

SkyPilot Cloud Consulting Inc.; San Mateo (CA); Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Competitive compensation and equity

Comprehensive medical, dental, vision

Company 401(k) plan

Gourmet lunch & dinner for the team

Job summary

SkyPilot Cloud Consulting Inc. in the San Francisco Bay Area is seeking an engineer to own the GPU and ML-systems layer that frontier AI teams run on.

You will manage accelerator scheduling, utilization, the serving path, and integrations that make SkyPilot the fastest, most cost-efficient platform for demanding AI workloads. You should have hands-on experience with GPU systems and ML training or inference infrastructure, strong Python, and a track record of production-scale ML systems work.

Qualifications

• Hands-on experience with GPU/accelerator systems and ML training/inference infra.
• Strong Python; systems-level and GPU-adjacent debugging.
• Experience with production-scale training or high-throughput inference.

Responsibilities

• Own GPU scheduling, utilization and health across clouds and Kubernetes.
• Build optimizations for training and serving, including checkpointing and autoscaling.
• Deepen integrations with vLLM, PyTorch, Slime, and related frameworks.

Skills

GPU systems

ML infrastructure

Python

Performance optimization

Production experience

Tools

Kubernetes

PyTorch

CUDA

KServe

Job description

SkyPilot Cloud Consulting Inc. in the San Francisco Bay Area is seeking an engineer to own the GPU and ML-systems layer that frontier AI teams run on.

You will manage accelerator scheduling, utilization, the serving path, and integrations that make SkyPilot the fastest, most cost-efficient platform for demanding AI workloads. You should have hands-on experience with GPU systems and ML training or inference infrastructure, strong Python, and a track record of production-scale ML systems work.