Kỹ Sư Nền Tảng Dữ Liệu CNTT

TP. Ho Chi Minh

Đăng ngày 19/03/2026

KEY RESPONSIBILITIES

ML Data Platform Engineering & Administration

Install, configure, and maintain ML data platforms on top of Kubernetes, Object Storage, Cassandra, Postgres and related technologies
Monitor platform performance and optimize as needed for reliability and efficiency

Platform Configuration and Maintenance

Implement and manage platform configurations, ensuring adherence to best practices and security standards
Regularly update and patch systems to maintain security and stability

Collaborate with Cross-Functional Teams

Work closely with ML and data engineers and other roles to align IT needs and strategies
Provide expert guidance on ML data platform best practices and optimization

Troubleshoot and Resolve Technical Issues

Backup and Recovery Management

Implement and maintain backup and recovery strategies for data platforms, ensuring data integrity and availability

Maintain and Update Documentation

Create and maintain documentation related to data platform administration, configuration, and maintenance
Share knowledge with team members and contribute to a culture of continuous learning

Enhance Data Security and Compliance

Ensure data platforms adhere to security best practices and comply with relevant regulations
Stay up-to-date on industry trends and evolving security standards

Drive Continuous Improvement

Evaluate and implement new technologies and techniques to enhance data platform performance and administration
Proactively identify areas for improvement, prepare plan for implementation and get support from management and development teams
Always prefer automation and code-first approach over hard to reproduce manual tasks

REQUIREMENTS

A degree in computer science, software engineering, information technology or related fields is preferred
Production use experience with AI agents (like Langchain, Agno) and LLM stack (like KServe, vLLM, pgvector)
At least 3 years of experience in data platform (Kafka, Spark, Airflow, Flink, KServe, MLFlow, Lakekeeper) and related infrastructure installation, administration, patching and automation (Linux, Ansible, Helm, Terraform, Kubernetes, Ceph)
Continuous improvement mindset covering daily operations, stability, reliability and performance of ML data platforms
Knowledge of key concepts like infrastructure-as-code, templates, playbooks, code versioning using GIT, CI/CD automation, high availability, disaster and recovery
Proficient in Linux Shell, Python scripting, configuration using JSON, YAML files
Ability to troubleshoot infrastructure, analyze logs and setup/update monitoring dashboards and metrics, describe and document root cause, attend retrospective meetings
Understand IT systems documentation, data flow diagrams, integration diagrams and related terminology (UML)
Understand major ML data platforms concepts – LLM, RAG, agent, quantization, fine-tuning, Data Lake, ACID, Distributed Query, Feature Store, Data Governance, Data Catalogue, Streaming, Batch , Parquet
Proficient in using documentation (Markdown, Visio, Office 365) and communication tools (MS Teams)
Proficient user of change management and support ticket/service desk tools (JIRA SD)

COMPENSATION & BENEFITS

If you are referred for this position by our Employee/Recruitment Collaborator, please apply via this LINK.

If you are an internal candidate, please apply via this LINK

Otherwise, please click the Apply button as below for application

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