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.