Lead MLOps

1. INTRODUCTION

a. About WAOHire:

WAOHire

company, is a collective group of tech recruiters and developers. We help fast growing companies connect with talented developers.

We take the humanized approach to hire and work with developers, because we know that's the best way to find the best developers for businesses.

2. RESPONSIBILITY:

We are looking for a highly skilled and hands-on MLOps & DevSecOps Engineer who can ensure smooth integration of AI/ML components, analytics pipelines, and backend systems into secure, scalable, and production-ready environments. This role requires deep expertise in DevOps automation, CI/CD pipelines, cloud infrastructure, container orchestration, and security best practices. The ideal candidate will work closely with data scientists, backend engineers, and product teams to operationalize AI models and analytics solutions efficiently and reliably.

Model Operationalization (MLOps):

• Collaborate with data scientists to containerize, deploy, and monitor ML models in production.
• Implement model registry, automated retraining, and continuous model delivery pipelines.
• Ensure reproducibility and scalability of ML workflows.

DevOps & Automation:

• Design, build, and maintain CI/CD pipelines for backend, data, and AI components.
• Manage containerized workloads using Docker and orchestrate deployments with Kubernetes or similar tools.
• Automate infrastructure provisioning using Terraform, Bicep, or equivalent IaC tools.

SecOps & Compliance:

• Implement robust security measures across all environments including container security, secret management, and vulnerability scanning.
• Ensure compliance with organizational and data governance standards.
• Manage secure access controls, logging, and monitoring systems.

Environment Management:

• Own the development, staging, and production environments for the Smart DC platform.
• Collaborate with engineering and analytics teams to ensure smooth deployment of new releases.
• Maintain high availability, scalability, and reliability across all environments.

Monitoring & Observability:

• Implement centralized logging, metrics, and alerting systems across services and ML components.
• Establish dashboards for model performance, system uptime, and pipeline health.

Collaboration & Best Practices:

• Work closely with data scientists, full stack engineers, and product managers to align release schedules and infrastructure needs.
• Enforce DevSecOps and software engineering best practices across the team.
• Participate actively in code and architecture reviews.

3. REQUIREMENTS

• Proven 6-8 years of experience in MLOps, DevOps, or SecOps roles managing production-grade systems.
• Proficient in English (both spoken and written).
• Willing to work onsite for 1 year in Singapore.

Strong hands-on skills in:

• CI/CD & Automation: Jenkins, GitHub Actions, or Azure DevOpsContainerization & Orchestration: Docker, Kubernetes
• Infrastructure as Code: Terraform, Bicep, or CloudFormation
• Monitoring & Logging: Prometheus, Grafana, ELK/EFK stacks, or Azure Monitor
• Security Tools: Vault, Trivy, Aqua, or equivalent
• Cloud Platforms: Azure (preferred) or multi-cloud environments
• Familiarity with machine learning lifecycle management tools such as MLflow, Kubeflow, or Azure ML.
• Strong understanding of cloud-native architecture, networking, and distributed systems.
• Experience with automated testing, canary releases, and rollback strategies.
• Excellent communication, debugging, and problem-solving skills, with a strong sense of ownership and accountability.

Preferred skills:

• Ability to understand the data center operational environment, predictive maintenance systems, and their integration with MLOps/DevOps pipelines would be highly beneficial.

4. BENEFITS:

Being a member of us, you will experience a youthful, flexible, and creative work environment

• Highly competitive salary 
  ($2500 - $3500 gross)
• Annual salary review.
• Working in a professional, friendly, well-equipped environment both with foreigners and Vietnamese.
• Extensive on job training, you will always have a chance to work with new emerging technologies.
• 12-day annual leave per year.

5. WORKING TIME:
Monday - Friday, 09:00 AM - 6:00 PM

6. INTERVIEW PROCESS:

1-2 rounds

7. LOCATION
: 1 year onsite in Singapore, then continue in office at District 2, HCMC