AI Support Engineer (Machine Learning)

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Technology, Data Science, or a related field, or equivalent practical experience.

• Three or more years of experience in machine learning engineering, DevOps, site reliability engineering, cloud engineering, software production support, or AI system operations.

• Experience independently supporting business-critical applications or services in a production environment.

• Strong working knowledge of at least one major cloud platform, such as AWS, Google Cloud Platform, or Microsoft Azure.

• Hands-on experience with container technologies and orchestration platforms such as Docker and Kubernetes.

• Experience with machine learning platforms or MLOps tools such as MLflow, Kubeflow, Vertex AI, SageMaker, or Azure Machine Learning.

• Proficiency with Python and SQL for troubleshooting, scripting, data investigation, and automation.

• Experience supporting CI/CD pipelines and infrastructure-as-code tools such as Terraform, CloudFormation, or equivalent technologies.

• Ability to investigate application logs, infrastructure metrics, distributed-system failures, data-quality issues, and service dependencies.

• Experience with incident management, problem management, root cause analysis, and production change-management practices.

• Strong analytical, troubleshooting, and communication skills.

• Ability to manage multiple priorities and make sound technical decisions in a fast-paced, 24/7 support environment.

• Ability to participate in an on-call rotation, including occasional support outside standard business hours.

• Strong English communication skills, including listening, speaking, and note-taking, with the ability to collaborate effectively in cross-functional teams.

Preferred Qualifications

• Experience with monitoring, observability, and alerting tools such as Prometheus, Grafana, Datadog, Splunk, Cloud Monitoring, or CloudWatch.

• Experience developing production-quality automation using Python, Bash, or another scripting language.

• Understanding of the complete machine learning lifecycle, including data preparation, model training, validation, deployment, monitoring, retraining, and retirement.

• Experience supporting real-time inference services, batch-scoring pipelines, generative AI applications, or AI agents.

• Familiarity with service-level indicators, service-level objectives, error budgets, and site reliability engineering practices.

• Experience with model monitoring, data drift, model drift, performance degradation, and AI-specific operational risks.

• Familiarity with secure software-development practices, identity and access management, secrets management, and cloud security controls.

• Experience mentoring junior engineers or leading technical incident investigations.

• Experience supporting globally distributed systems, teams, or customers.

Why You'll Love Working Here 100% salary during probation period Annual Leave: 18 days/ year Five “Recharge Days” – Extra days, in addition to company holidays. 2 days WFH/ weef Flexible Friday afternoon Full salary insurance 13th-month bonus 1 day off for birthday Advanced health insurance (Generali) Regular engagement activities: sport clubs, internal event… Support Macbook and Monitor

Working location: Waseco building, 10 Pho Quang, Tan Son Hoa ward, Ho Chi Minh city, Vietnam.