AI Engineer
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Job Summary
Company Type:
Product
Technical Skills:
Machine Learning
Location:
Ho Chi Minh - Viet Nam
Working Policy:
Hybrid
Salary:
Negotiation
Job ID:
J01743
Status:
Close
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- Network
Operate and evolve our Kubernetes platform across multiple clusters and environments (Prod, Dev, hybrid on-prem and public cloud), covering control plane operations, node lifecycle, upgrades, and autoscaling at every layer (Cluster Autoscaler, HPA, KEDA). Architect and manage hybrid cloud infrastructure spanning on-premises and public clouds (GCP, AWS), including workload placement, cross-cloud networking, and unified resource management. Own the CI/CD and GitOps experience end-to-end: container build pipelines, image optimization, and progressive delivery via ArgoCD / FluxCD. Own the observability stack as a single pane of glass across all clusters: Grafana, Mimir, Tempo, Loki, Pyroscope, OnCall, Prometheus -- and help push toward agent-assisted SRE workflows. Manage and improve our inference platform: vLLM serving and AIBrix for multi-model orchestration and autoscaling across a fleet of NVIDIA GPUs. Operate platform services: Kafka, Redis, PostgreSQL, OpenSearch. Manage identity and access via Keycloak integrated with Google Workspace; harden SSO, RBAC, and secrets management across the platform. Harden network security across private load balancers, firewalls, and VPC segmentation; design and maintain hub-and-spoke / multi-AZ topologies. Support training infrastructure: self-service VM provisioning, RunPod burst capacity, Weights and Biases integration. Drive infrastructure reliability, cost efficiency, and capacity planning as the platform scales.
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Build and maintain distributed infrastructure handling telemetry, sensory, and control data across cloud and edge environments Design and operate data ingestion and streaming pipelines connecting robot fleets to the cloud in real time, covering video, joint states, audio, and LiDAR Develop and maintain backend services and APIs that power the Company's developer-facing platform, with a focus on reliability and developer experience Manage and evolve cloud native infrastructure using Kubernetes, Docker, and infrastructure as code tooling Ensure platform reliability through monitoring, alerting, autoscaling, failover, and incident response Support ML and robotics teams with data infrastructure for training pipelines, policy rollout, and hardware-in-the-loop simulation Implement secure APIs with access control, rate limiting, and usage metering as we scale
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