Senior MLOps & Infrastructure Engineer

About the Role

We are looking for Senior

MLOps

& Infrastructure Engineers to build and operate the hybrid AI computing platform behind VinFast’s ADAS and autonomous driving

programme

-

on-premise

GPU clusters running perception model training and large-scale inference, a multi-petabyte sensor data archive, and the platform services used daily by our engineering and annotation teams.

What the Team Covers

You will contribute across

all of

the following over time. We do not expect one person to master every part on day one, but we do expect you to be willing to work in any of them.

• GPU and HPC clusters running model training, large-scale inference and annotation workloads

• MLOps

  model serving, pipeline orchestration, experiment and model registry

• Storage at multi-petabyte scale: tiering, lifecycle, backup and recovery

• Ingestion of large volumes of recorded sensor data, with integrity verification and metadata extraction

• CI/CD,

  GitOps

  , infrastructure-as-code, monitoring and observability

• Access control, audit logging and data protection for internal and external users

Key Responsibilities

AI Compute & Serving

• Operate and scale GPU clusters across training, inference and annotation workloads; manage scheduling,

  utilisation

  and capacity

• Deploy and scale high-throughput model serving; tune GPU memory and runtime performance

• Manage multi-GPU distributed training and reproducible environment sandboxing

• Scale pipeline orchestration on Kubernetes for large data processing jobs

Platform Automation & Delivery

• Drive

  GitOps

  -based deployment and maintain infrastructure-as-code across the platform

• Build and maintain CI pipelines, secure container builds and release automation

• Build monitoring, logging and alerting so that failures are detected and actionable, never silent

• Lead incident response and drive follow-up actions to closure

Data Infrastructure & Security

• Operate storage at multi-petabyte scale: object storage, local storage, tiering, backup and recovery

• Operate the ingestion path for large sensor data deliveries, with integrity verification and metadata extraction

• Implement access control and single sign-on across platform services, with audit logging

• Apply data protection measures to sensitive content before it reaches external users

Requirements

• 4+ years in MLOps

  , DevOps, SRE or HPC platform engineering

  , with production ownership of AI/ML infrastructure

• Kubernetes

  administration at production scale: Helm, ingress (

  Traefik

  or Envoy), CNI, and

  GitOps

  (Flux or

  ArgoCD

  )

• GPU & HPC

  SLURM, NVIDIA Container Toolkit, CUDA runtime tuning, multi-GPU memory debugging

• Strong Linux systems skills

  and infrastructure-as-code (

  SaltStack

  or Ansible)

• Python and Bash

  for automation, including Airflow DAGs and custom operators

• Object storage, and a monitoring and logging stack (Prometheus, Grafana or equivalent)

• Willingness to work across the full stack

  • compute, storage, networking, automation and security - rather than within a single specialty

• Good communication in English - technical documentation and working with international partners

Benefits

• Competitive salary

• Premium healthcare package, including PVI insurance & annual health check-ups

• 13th-month salary & performance bonuses to reward your contributions

• Enjoy preferential pricing for services within the Vingroup ecosystem including Vinmec, Vinpearl, and Vinschool...

• Opportunity to collaborate with and learn from industry-leading professionals in the automotive domain

• Work Location:

  Technopark Tower, Gia Lam, Ha Noi

​ With respect to all your personal data shared to VinFast in the application and the entire recruitment process of VinFast, by clicking “Apply”, submitting your resumé/CV and/or participating in VinFast's recruitment process, you agree that you have read VinFast's Personal Data Protection Policy ("Policy") posted at https://vinfastauto.com/vn_vi/dieu-khoan-phap-ly or https://vinfast.vn/privacy-policy/ , you agree to the Policy and consent for VinFast to process your personal data in accordance with the Policy and the applicable regulations on personal data protection.