Lead AI Infra Engineer: GPU Compute & ML Pipelines, Equity

Fuel Talent; Seattle (WA); On-site; USD 180,000 - 210,000; Full time

Job summary

Fuel Talent in Seattle is seeking an AI Infrastructure Engineer to lead the 0-to-1 build of the core compute and orchestration layer for ML workloads. You will own GPU orchestration and resource management, shaping engineering standards from day one.

You will design researcher-friendly SDKs/APIs, operationalize ML pipelines, and partner with customers to improve model performance and observability, while guiding the tech roadmap and security posture.

Qualifications

• 5+ years of software engineering experience focused on ML infrastructure or backend systems.
• Proficiency in Golang, Python, or Typescript.
• Deep Kubernetes experience for GPU workloads on AWS/GCP.
• Experience deploying ML training or inference pipelines in production (PyTorch, Hugging Face).

Responsibilities

• Architect the GPU compute fabric and orchestration layer for ML workloads.
• Design SDKs and APIs to streamline ML workflows for researchers.
• Operationalize end-to-end ML pipelines from data ingestion to model serving.
• Collaborate with customers to debug jobs and build observability tools.
• Lead the technical roadmap and influence infra and security decisions.

Skills

ML infra

Golang

Python

Typescript

Kubernetes

System design

Tools

AWS

GCP

PyTorch

Hugging Face

Job description

Fuel Talent in Seattle is seeking an AI Infrastructure Engineer to lead the 0-to-1 build of the core compute and orchestration layer for ML workloads. You will own GPU orchestration and resource management, shaping engineering standards from day one.

You will design researcher-friendly SDKs/APIs, operationalize ML pipelines, and partner with customers to improve model performance and observability, while guiding the tech roadmap and security posture.