ML Ops / Dev Ops Engineer

📋 Description

• Infrastructure & Automation Strategy: Drive automated deployment/validation workflows for AI/vision initiatives.
• Video Pipeline Operations: Design/manage infra for real-time video streams at scale.
• Systems & Networking Core: Maintain Linux environments; architect cloud/edge video networking.
• CI/CD & Deployment: Design pipelines; automate provisioning; deploy microservices with Helm.
• Reliability & Monitoring: Build monitoring/alerting for AI/video workloads.
• Collaboration & Scaling: Collaborate with ML engineers to validate models and scale deployments.

🎯 Requirements

• Education: BS, MS, or PhD in Computer Science or related field.
• Experience: 4+ years in DevOps, MLOps, or Systems Engineering.
• Systems & Networking Mastery: Linux admin, kernel tuning, TCP/IP, VPNs, firewalls.
• Data & Video Pipelines: Video streaming RTSP/HLS/WebRTC or real-time data pipelines.
• Cloud-Native & CI/CD: Kubernetes, Helm, and CI/CD (Jenkins/GitLab/ArgoCD).
• Infrastructure as Code: Terraform, Ansible.

🎁 Benefits

• Competitive base salary + equity options.
• Comprehensive health, dental, and vision benefits.
• Opportunity to build infra for Physical AI and computer vision.