Kubernetes ML and Cloud AI Jobs (2026)
Kubernetes has become the backbone of production ML infrastructure. These roles focus on building and managing cloud-native ML systems, from training clusters to model serving platforms, using Kubernetes, Kubeflow, and related cloud-native technologies.
Last updated: October 2, 2026
Latest Kubernetes ML Jobs
View all jobsSenior Cloud AI Architect
Cloud AI Solutions Engineer
Senior Researcher (m/w/d/x) Edge-Cloud AI-Plattform
Unlock the apply link on every AI job
Browsing is free. Membership is $9 a year or $4.90 every three months and unlocks the apply link and the full description on every job. Cancel any time from your billing page.
- The apply link on every job, straight to the official posting
- Full job descriptions instead of the preview
- Every AI job, every day: thousands of listings from 1,000+ company career pages
- Save jobs and get daily alerts for your categories
Secure checkout by Dodo Payments·Cancel anytime from your billing page
Data Platform Engineer (Kubernetes & MLOps)
Software Engineer III, AI/ML, Google Cloud AI
Staff Software Engineer, AI/ML GenAI, Google Cloud AI
Software Engineer III, AI/ML GenAI, Google Cloud AI
Senior Software Engineer, AI/ML GenAI, Google Cloud AI
Cloud AI Engineer
Senior Staff Software Engineer, AI/ML GenAI, Google Cloud AI
Senior Software Developer, AI/ML GenAI, Google Cloud AI
Kubernetes AI Task Auditor - Freelance AI Trainer Project
Python and Kubernetes Software Engineer - Data, Workflows, AI/ML & Analytics
Senior Staff Software Engineer, Cloud AI Infrastructure
Senior Staff Software Engineer, Cloud AI Infrastructure
Python and Kubernetes Software Engineer - Data, Workflows, AI/ML & Analytics
Staff Product Manager, Rubrik Security Cloud AI Platform
Site Reliability Engineer - AI & ML Infrastructure (Kubernetes, AWS & Terraform)
Platform Engineer - AI/ML Infrastructure (Kubernetes, Slurm & Bare-Metal)
Platform Engineer - AI/ML Infrastructure (Kubernetes & Terraform)
Frequently Asked Questions
Why is Kubernetes important for ML?
Kubernetes orchestrates GPU clusters for distributed training, manages model serving at scale, enables reproducible ML pipelines, and provides the foundation for ML platforms like Kubeflow. Most major companies run their ML infrastructure on Kubernetes, making it a critical skill for MLOps and ML infrastructure engineers.
What Kubernetes ML skills are in demand?
Key skills include Kubernetes cluster management, GPU scheduling and resource management, Kubeflow pipelines, KServe/Seldon for model serving, Helm charts, Terraform for IaC, and experience with managed Kubernetes services (EKS, GKE, AKS). Knowledge of NVIDIA GPU Operator and multi-GPU training is highly valued.
AI Job Insights for Kubernetes ML Jobs
Salary Range (Yearly, USD)
$60K - $414K
Median $138K from 79 listings with salary data
Top Companies Hiring
Based on recent listings shown on this page.
Common Roles
Counts reflect recent listings, not total market size.
In-Demand Skills
Derived from tags on recent listings.
Explore More AI Job Paths
Top Cities
Explore More AI Job Categories
MLOps Jobs
Find MLOps and ML Infrastructure roles. Build the platforms that power AI systems.
AI Infrastructure Engineer Jobs
Find AI infrastructure positions. Build the compute and platform layer powering AI systems.
AWS AI Jobs
Find AI roles requiring AWS, GCP, or Azure cloud AI platform expertise.
Machine Learning Jobs
Find ML Engineer positions at top companies. Build and deploy production ML systems.