Location: Hanoi, VietNam
Project Type: AI Engineering (Model Integration and Deployment)
Language Requirement: Fluent English (spoken and written)
About the Role
We are seeking a software-minded ML Engineer to join our team of AI Engineers (AIEs) who are responsible for deploying, integrating, and wrapping ML models as scalable, production-ready solutions without developing or training models.
The ideal candidate is a strong Python developer who treats ML models as black-box services, with a solid grasp of data workflows and a professional software engineering mindset.
Key Responsibilities
- Wrap, deploy, and manage pre-built ML models using Python and Kubeflow.
- Build data preprocessing and postprocessing pipelines to support ML inference.
- Collaborate with Data Scientists, ML Ops, and Platform Engineers to ensure smooth integration and scalable solutions.
- Write clean, maintainable, and scalable code adhering to software engineering best practices.
- Think through edge cases, ensure robustness, and deliver sustainable solutions not quick fixes.
- Document processes and contribute to reusability and generalization of AI components.
Required Skills & Qualifications
- Strong software engineering experience.
- Proficiency in Python and common development practices (e.g., Clean Code, version control, unit testing).
- Good understanding of ML/AI workflows and data lifecycle, especially around data preparation, preprocessing, and delivery.
- Familiarity with containerization tools such as Docker.
- Fluent English communication skills (written and verbal) must.
Nice to Have (Learnable on the Job)
- Experience with Kubeflow on Kubernetes for model orchestration.
- Understanding of CI/CD pipelines (e.g., GitHub Actions).
- Exposure to AWS cloud services for deployment or data handling.
This Role is NOT About
- Designing or training ML models.
- Research-focused or academic data science work.
