Senior AI Systems Engineer - Multi-Cloud HPC

Archer; San Jose (CA); On-site; USD 172,800 - 216,000; Full time

Job summary

Archer, an aerospace company in San Jose, seeks a Staff AI Systems Engineer to architect and manage infrastructure for large-scale AI model training and low-latency inference. You will bridge data and high-performance AI models, deploying resilient multi-cloud systems and optimizing LLM serving engines.

You will work with AI researchers and software engineers to productionize models, monitor bottlenecks, and ensure scalable compute strategies across cloud and bare-metal environments.

Qualifications

• Education: BS/MS/PhD in Computer Science, Software Engineering, or related field.
• Experience: 5+ years of professional software engineering focused on AI/ML systems, HPC, or ML infrastructure.
• Familiarity with hyper-scaler infrastructure (AWS) and AI-centric clouds (Nebius AI Cloud).
• Hands-on with containerization (Docker) and production orchestration (Kubernetes) and cloud-agnostic cluster abstraction (SkyPilot).
• Knowledge of LLM serving optimization using frameworks like vLLM and SGLang.
• Data engineering for AI: high-throughput data pipelines; SQL, NoSQL, Parquet.

Responsibilities

• Architect, deploy, and manage infrastructure services for large-scale AI model training and inference.
• Deploy, scale, and manage resilient infra for distributed AI training and low-latency inference.
• Utilize MLflow for experiment tracking and model registry to streamline AI lifecycle.
• Optimize compute and inference, manage multi-cloud compute scheduling, and LLM serving engines.
• Collaborate with AI researchers and software engineers to productionize models and monitor performance.

Skills

AI systems

HPC

ML infrastructure

Docker

Kubernetes

SkyPilot

vLLM

SGLang

SQL/NoSQL/Parquet

Education

BS/MS/PhD in CS/SE

Tools

AWS

Nebius AI Cloud

Nebius AI Cloud

SkyPilot

Job description

Archer, an aerospace company in San Jose, seeks a Staff AI Systems Engineer to architect and manage infrastructure for large-scale AI model training and low-latency inference. You will bridge data and high-performance AI models, deploying resilient multi-cloud systems and optimizing LLM serving engines.

You will work with AI researchers and software engineers to productionize models, monitor bottlenecks, and ensure scalable compute strategies across cloud and bare-metal environments.