Megazone

Tóm tắt công việc

MEGAZONE Vietnam is looking for a highly skilled AI Engineer with strong experience to join our dynamic global team. The ideal candidate will be responsible for building, and optimizing large-scale data pipelines, ensuring scalability, performance, and reliability. You will collaborate closely with offshore teams at MEGAZONE CLOUD and external partners

What You Will Do:

• Collaborate with AI engineers, data scientists, and business stakeholders to understand ML-specific data requirements and deliver clean, reliable, well-architectured datasets.
• Design, build, and maintain feature engineering pipelines and feature stores for machine learning models.
• Build low-latency, scalable pipelines for both batch and real-time AI workloads.
• Automate model training, deployment, and monitoring using AWS SageMaker, MLflow, or similar tools.
• Build data ingestion pipelines from structured and unstructured data sources (e.g., APIs, databases, files, streaming data).
• Mentor junior engineers and review code to ensure best engineering practices are followed.

• The attractive salary (Negotiation)
• 2-month probation period with 100% salary.
• Full salary insurance coverage after the probation period.
• Participation in the PVI health insurance package, and annual health check-ups.
• 13th-month salary, birthday bonus, New Year bonus, Mid-Autumn Festival gifts, March 8th and October 20th gifts, etc.
• Performance evaluation and regular salary increases.
• Welfare for personal events, childbirth, and other benefits as per labor regulations and company welfare policies.
• Dynamic and youthful work environment conducive to personal growth and development.

Working Time And Location

• Company: Megazone Vietnam
• Working Hours:
  • Standard: 8:30 AM – 5:30 PM (Lunch: 12:00 PM – 1:00 PM), Monday to Friday
  • Flexible working hours may apply depending on project (e.g., 1:00 PM – 9:00 PM)
• Location:
  • 27th Floor, East Tower, Lotte Center Hanoi, 54 Lieu Giai, Ba Dinh District, Hanoi, Vietnam

Basic Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or related field.
• 3+ years of experience in AI, data engineering or a related field.
• Knowledge of data modeling for AI, including feature stores and time-series datasets.
• Strong proficiency in SQL and Python skills.
• Experience with cloud platforms: AWS, Azure, or GCP (preferably AWS).
• Familiarity with CI/CD, Git, and DevOps practices for data and ML systems.
• Strong understanding of data security, privacy, and compliance practices.

Preferred Qualifications

• Experience with real-time data processing ( Kafka, Kinesis, Spark Streaming..).
• Hands-on experience with AWS SageMaker, MLflow, or Kubeflow.
• Familiarity with data lakehouse and cloud data warehouse concepts.
• Exposure to machine learning pipelines and MLOps concepts
• Understanding of MLOps best practices and AI model lifecycle management.
• Knowledge of data governance frameworks and metadata management.