Senior ML Infra Engineer - Kubernetes & EKS

Amazon Inc.

Santa Clara (CA)

Sur place

USD 193 000 - 262 000

Plein temps

14 jours+

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Résumé du poste

Amazon Inc. is seeking an experienced software engineer to build and operate an infrastructure platform for training, fine-tuning and inference of AI models within the EKS ecosystem.

You will collaborate across AI teams to operationalize models and enhance the EKS experience for customers. The role emphasizes scalable, reliable infra, ML pipelines and strong software engineering practices.

Qualifications

  • Bachelor's degree in computer science or equivalent.
  • 8+ years of non-internship professional software development experience.
  • 5+ years of programming with at least one major language.
  • 5+ years in design/architecture of scalable systems.
  • Experience mentoring or leading teams.
  • Strong fundamentals in CS, data structures and algorithms.
  • Proficiency in Java, Go, C/C++, Python, or Perl on Linux.

Responsabilités

  • Build and operate an infrastructure platform for training, fine-tuning and inference of AI models.
  • Collaborate with AWS AI teams to operationalize models and improve EKS experience.
  • Contribute to open-source projects like AWS VPC CNI and eBPF-based tooling.
  • Define technical strategy and oversee high-scale, reliable infrastructure development.
  • Work with Kubernetes and ML frameworks like PyTorch, JAX, Kubeflow, and Kueue.

Connaissances

Java
Golang
Python
C/C++
Linux
Distributed systems
Kubernetes
PyTorch/JAX/Kubeflow

Formation

Bachelor's degree in computer science or equivalent

Outils

Linux kernel
eBPF
Kubernetes

Description du poste

Amazon Inc. is seeking an experienced software engineer to build and operate an infrastructure platform for training, fine-tuning and inference of AI models within the EKS ecosystem.

You will collaborate across AI teams to operationalize models and enhance the EKS experience for customers. The role emphasizes scalable, reliable infra, ML pipelines and strong software engineering practices.

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