Senior Cloud Infrastructure Engineer for ML Platforms

Fireworks AI; United States; On-site; USD 180,000 - 260,000; Full time

Job summary

Fireworks AI seeks a Software Engineer for its Cloud Infrastructure team to architect and build foundational systems powering a cutting-edge generative AI platform.

The role focuses on creating a scalable, reliable backend for distributed training, inference, and data processing, across cloud providers. You will lead design discussions, mentor engineers, and advance IaC, CI/CD, and observability to ensure performance and cost-efficiency.

Qualifications

• 5+ years designing and building backend infrastructure in cloud environments (AWS, GCP, Azure).
• Proven experience in ML infrastructure and tooling (PyTorch, TensorFlow, Vertex AI, SageMaker, Kubernetes).
• Strong programming in Python and/or C++.
• Bachelor’s degree in CS/Engineering or equivalent practical experience.
• Master’s or PhD in CS or related field.
• Experience leading infrastructure projects for large-scale ML/AI workloads.
• Familiarity with IaC and CI/CD tooling (Terraform, ArgoCD, GitOps).
• Open-source contributions to cloud or ML infra projects a plus.

Responsibilities

• Architect and build scalable, low-latency backend infrastructure for distributed training and inference.
• Lead technical design discussions and mentor other engineers.
• Collaborate with ML, DevOps, and product teams to translate research into robust infra solutions.
• Drive reliability, observability, and cost-efficiency across multi-cloud systems.

Skills

ML infrastructure

Python

C++

Distributed systems

Cloud platforms

Education

Bachelor’s or higher in CS/Engineering

Master’s or PhD in CS or related field

Tools

Kubernetes

Kubeflow

MLFlow

Terraform

ArgoCD

Job description

Fireworks AI seeks a Software Engineer for its Cloud Infrastructure team to architect and build foundational systems powering a cutting-edge generative AI platform.

The role focuses on creating a scalable, reliable backend for distributed training, inference, and data processing, across cloud providers. You will lead design discussions, mentor engineers, and advance IaC, CI/CD, and observability to ensure performance and cost-efficiency.