201 open roles · refreshed hourly
Kubernetes ML Jobs
Orchestrate ML at scale. We aggregate positions requiring Kubernetes expertise for ML training, serving, and infrastructure.
Latest roles
Latest Kubernetes ML roles
Incident Response Engineer
10/16Snowflake • Remote
Incident ResponseSecurity InvestigationsIncident Command+21+20+19$143k – 206kAI/ML Engineer II - Remote
10/15Torentify • Remote
C#PythonAzure+38+37+36$120k – 215kAI Security Specialist
10/15Suno • New York City, NY
PythonGoIam+19+18+17$277k – 364k- G
Applied AI Engineer
10/15GSK • Cambridge +5
PythonPyTorchTensorFlow+46+45+44$136k – 227k Forward Deployed Engineer - New Grad (2027)
10/15Applied Intuition • Sunnyvale, CA
C++PythonReact+17+16+15$130k – 158k- TI
AI Engineering Lead
10/15TRUBRIDGE, INC. A CORPORATION OF OHIO • Fort Lee, NJ
PythonPyTorchTypeScript+42+41+40$250k+ Staff AI/ML Platform Engineer
10/15Abbott • Alameda, CA
PythonAzure Ml SdkAzure Data Factory+29+28+27$114k – 228kSr Engineer, Commercial AI Forward Deployment
10/15T-Mobile • Bellevue, WA
PythonGoTypeScript+25+24+23$142k – 257kSenior Software Engineer - Identity, Data Security and Trust
10/15Snowflake • Remote
JavaC++Python+31+30+29$200k – 288kTechnical Program Manager, Inference
10/15Anthropic • San Francisco, CA +1
Technical Program ManagementInference InfrastructureDistributed Systems+29+28+27$290k – 435kEngineering Manager Runtime - Storage
10/15Baseten • Remote
GoRustC+21+20+19$165k – 330kClient Platform Engineer
10/15OpenAI • Remote
PythonGoLinux+30+29+28$347k – 445k
Career guide
Why Kubernetes for ML?
ML Infrastructure
- Orchestrate training jobs at scale
- Kubeflow for ML workflows
- KServe for model serving
- GPU scheduling and management
- Standard for production ML
Platform Engineering
- Build ML platforms for teams
- Multi-cloud and hybrid deployments
- Resource optimization and cost control
- CI/CD for ML models
- Path to ML platform leadership
K8s ML Compensation
Kubernetes + ML expertise is highly valuable for platform roles. Senior K8s ML engineers earn $180k-$320k+ at companies scaling AI infrastructure.
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