Senior GPU Platform Engineer — Remote

STN Inc; Poland; Hybrid; PLN 530,705 - 720,242; Full time

Job summary

STN Inc. is seeking a Senior Platform Engineer to design and operate the multi-tenant orchestration layer that turns raw GPU infrastructure into a usable cloud service. You will help build the backbone of GPUaaS with Kubernetes, Run:ai, and related tooling.

You will own multi-tenant isolation, platform APIs, image management, and automation, collaborating with SRE and TAM teams to ensure reliability and scalable growth. Remote US or hybrid in Pleasanton, CA options are supported.

Qualifications

• 6+ years in platform engineering, SRE, or cloud engineering at scale.
• Deep Kubernetes expertise including CRDs, operators, and multi-tenant patterns.
• Strong programming skills in Go, Python, or both.
• Experience operating GPU clusters or AI infrastructure at production scale.
• Bachelor's degree in computer science or equivalent experience.

Responsibilities

• Design and build the orchestration layer (Kubernetes, Slurm, Run:ai, or comparable)
• Manage multi-tenant isolation including namespaces, networking, storage, and quotas
• Build customer-facing platform APIs, CLIs, web portals, and SDKs
• Implement and operate image management, GPU operator, and node provisioning automation
• Drive infrastructure-as-code and automation across the platform stack
• Partner with SRE on platform reliability, SLO definition, and observability
• Support TAM and Support engineers on customer-impacting platform issues
• Maintain customer environment templates, configuration management, and rollout tooling
• Participate in architecture review, design discussions, and technical roadmap
• Drive continuous platform improvement and reduce operational toil

Skills

Kubernetes

Go

Python

Education

Bachelor's degree in computer science

Tools

NVIDIA GPU Operator

MIG

MPS

NCCL operator

Slurm operator

Run:ai

KubeRay

Job description

STN Inc. is seeking a Senior Platform Engineer to design and operate the multi-tenant orchestration layer that turns raw GPU infrastructure into a usable cloud service. You will help build the backbone of GPUaaS with Kubernetes, Run:ai, and related tooling.

You will own multi-tenant isolation, platform APIs, image management, and automation, collaborating with SRE and TAM teams to ensure reliability and scalable growth. Remote US or hybrid in Pleasanton, CA options are supported.