Infrastructure Engineer

Infrastructure Engineer - Video Generation

About Us

We are a cutting-edge AI startup specializing in next-generation video generation technology based in Hong Kong. Our mission is to push the boundaries of what's possible in AI-driven video generation through innovation of foundation model. As a growing startup, we offer a dynamic environment where your research can have immediate impact on technology development.

Position Overview

We are seeking an experienced Infrastructure Engineer to architect and manage our AI computing infrastructure. The ideal candidate will have extensive experience in building and scaling ML infrastructure, with particular emphasis on distributed training systems and GPU cluster management.

Key Responsibilities

Design and implement high-performance computing infrastructure for large-scale AI model training

Manage and optimize GPU clusters for distributed training workloads

Build and maintain container orchestration systems for ML workflows

Implement efficient resource allocation and scheduling systems

Design and maintain monitoring and alerting systems for compute infrastructure

Optimize infrastructure costs while maintaining performance

Collaborate with ML teams to support their computing needs

Ensure system reliability, security, and scalability

Required Qualifications

Master's degree in Computer Science, Systems Engineering, or related field

8+ years of experience in infrastructure engineering, with focus on ML/AI infrastructure

Strong experience with:

GPU cluster management and optimization

Kubernetes and container orchestration

Linux system administration

Infrastructure as Code (IaC)

Proven track record in building large-scale computing systems

Experience with major cloud providers (AWS/GCP/Azure or Alibaba Cloud/Tencent Cloud etc)

Preferred Qualifications

Experience with ML infrastructure at major tech companies

Knowledge of distributed training systems (PyTorch DDP, Horovod)

Familiarity with ML frameworks and their infrastructure requirements

Experience with high-performance networking (InfiniBand, RDMA)

Background in performance optimization and troubleshooting

Understanding of ML workload characteristics

Bilingual proficiency (English/Chinese)

Technical Skills

Computing Infrastructure

GPU Clusters: NVIDIA DGX, GPU management tools

Distributed Systems: Slurm, Kubernetes

ML Platforms: Kubeflow, Ray

Job Scheduling: YARN, Slurm

Cloud & Networking

Cloud Platforms:

International: AWS, GCP, Azure

China: Alibaba Cloud, Tencent Cloud

Networking: InfiniBand, RDMA, TCP/IP optimization

Load Balancing: HAProxy, NGINX

Infrastructure Management

Container Technologies: Docker, Kubernetes, Singularity

IaC: Terraform, Ansible, CloudFormation

CI/CD: Jenkins, GitLab CI

Monitoring: Prometheus, Grafana, ELK Stack

Development

Languages: Python, Go, Shell scripting

Version Control: Git

Documentation: Markdown, Confluence

What We Offer

Opportunity to build cutting-edge AI infrastructure

Competitive salary and equity package

Access to latest hardware and technologies

Professional development opportunities

Comprehensive health benefits

Learning and conference budget

Location

Hong Kong (on-site, Hong Kong Science and Technology Park)

Expected Impact

Design and implement next-generation AI computing infrastructure

Optimize resource utilization and cost efficiency

Improve training speed and efficiency for AI models

Build scalable and reliable systems

Projects You'll Work On

Building automated GPU cluster management systems

Implementing efficient resource scheduling for ML workloads

Optimizing distributed training infrastructure

Setting up monitoring and observability systems

Designing disaster recovery and backup solutions

To Apply:

Please submit:

Detailed CV highlighting relevant infrastructure projects

Description of the largest scale system you've built/managed

Examples of infrastructure optimization achievements

Professional references

To apply or learn more about this position, please contact [HIDDEN TEXT].