Principal MLOps Engineer
Remote, US; DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI
R
USD 150K-200K Senior-level Full Time
Tasks
- Build deployment pipelines for production machine learning
- Deploy and manage machine learning workloads on Kubernetes
- Design secure scalable MLOps infrastructure
- Implement CI CD workflows for ML services and artifacts
- Improve observability reliability security and maintainability
- Maintain model lifecycle monitoring and operational support
- Provision and troubleshoot Kubernetes clusters in production
- Standardize runtime patterns serving frameworks and deployment architectures
- Support compliance driven secure software supply chain requirements
Perks/Benefits
- 401k match
- Annual tech budget
- Education & training benefits
- Flexible work options
- Health, dental, vision coverage
- Hybrid work options
- Paid Holidays
- Paid Snacks
- Paid time off
- Referral bonuses
- Remote work options
- Team offsite
- Tech gadgets budget
- Travel opportunities
Skills/Tech-stack
AWS | Azure | CI/CD | Container hardening | Docker | GPU | Git | Helm | Inference | Inference Server | Infrastructure as Code | Istio | Istio Service Mesh | KServe | Kubeflow | Kubernetes | MLOps | Machine Learning | Model Serving | Monitoring | Observability | Python | Ray Serve | Runtime Scanning | Security | Service Mesh | Supply Chain | Supply chain security | Terraform | Triton Inference | Triton Inference Server | VLLM | Vulnerability Management | “as-code”
Education
N/A
Roles
Engineer | MLOps Engineer | Principal | Principal MLOps Engineer
Regions
Countries
States
Florida, US | Texas, US | Colorado, US | Hawaii, US | Massachusetts, US | Virginia, US
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