ML Training Platform Engineer | Multi-Cloud & Decentralized

Pluralis Research; San Francisco (CA); Remote; USD 120,000 - 160,000; Full time

Job summary

A decentralized AI platform company in the United States is seeking an experienced ML Training Platform Engineer to design and build robust infrastructure for ML training. The ideal candidate has over 5 years in infrastructure and platform engineering, with expertise in multi-cloud deployments and distributed systems. Responsibilities include architecting fault-tolerant infrastructure and simulating real-world network conditions. This role is essential for enabling large-scale, collaborative AI development.

Qualifications

• 5+ years of experience with deep experience in infrastructure and platform engineering.
• Production experience managing multi-cloud deployments.
• Strong Python engineering skills with a focus on reliability and observability.

Responsibilities

• Design resource management systems across AWS, GCP, and Azure.
• Architect fault-tolerant infrastructure for distributed ML.
• Build systems simulating real-world network conditions for ML training.

Skills

Infrastructure & Platform Engineering

Distributed Systems & ML Infrastructure

Systems Programming & Reliability

Tools

Pulumi

Terraform

Docker

Kubernetes

Prometheus

Grafana

Job description

A decentralized AI platform company in the United States is seeking an experienced ML Training Platform Engineer to design and build robust infrastructure for ML training. The ideal candidate has over 5 years in infrastructure and platform engineering, with expertise in multi-cloud deployments and distributed systems. Responsibilities include architecting fault-tolerant infrastructure and simulating real-world network conditions. This role is essential for enabling large-scale, collaborative AI development.