Job description
Directly build and maintain hybrid MLOps infrastructure, develop automated pipelines (CI/CD/CT) ensuring critical models operate stably, accurately with minimal latency serving business needs
1. Directly develop, integrate and optimize Feature Pipelines ensuring data readiness for both Batch and Real-time computation flows
Configure data transformation flows to provide accurate inputs for models
2. Refactor into standard OOP Production code. Dockerize models and build prediction Endpoints (REST API / gRPC) using high-performance frameworks such as FastAPI, Triton Inference Server
Build and maintain automated CI/CD pipelines; implement non-disruptive deployment strategies (Blue/Green, Canary)
3. Set up Dashboards monitoring system metrics (CPU, RAM, Latency, Throughput) and prediction quality (Data Drift, Concept Drift)
Build and configure Continuous Training (CT) flows to automatically collect new data and retrain when model performance degrades
Directly diagnose and resolve incidents (Incident Troubleshooting) related to ML application layer
4. Participate in building source code standards (Coding Guidelines) and internal handover regulations (SOP)
Requirements
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics or related fields
- Minimum 03 years of practical experience in Machine Learning Engineer, Data Engineer or Backend Engineer positions with expertise in AI/ML deployment
- Proficient in Python (OOP, Design Patterns), SQL. Strong experience developing APIs with FastAPI or Flask. Solid grasp of Containerization technology (Docker, Kubernetes). Experience setting up CI/CD pipelines (GitLab CI, GitHub Actions)
- Have worked with Experiment Tracking systems (MLflow, Weights & Biases) and knowledge of Feature Store (Hopsworks, Feast). Ability to configure Serving Engines (Triton, TorchServe) is a major advantage
- Priority given to candidates who have directly deployed Credit Risk analysis models or behavioral analysis models in Finance - Banking industry
BENEFITS:
- Personal and family health insurance
- Travel
- Fitness Center (Yoga, GYM,...)
- Support for sports training, transportation, childcare/kindergarten, phone allowances
- Regular health check-ups
- 13th month salary
- Birthday leave
- Holiday bonuses (Tet, National Day, 30/4 - 1/5, Bank Anniversary,...)
- Performance bonuses, Performance incentives
- Preferential loans
MB Bank requires applicants to provide the following detailed information:
- Personal information: Full name, Date of birth, Gender
- Phone number and Email contact
- Education level, School graduated from
- Work experience
- 3 - 5 outstanding skills
Why should you ensure complete information when applying?
- Your profile will be evaluated quickly.
- For profiles with complete information and matching recruitment criteria, MB Bank will proactively contact for interview at the earliest time.
- Applicants please check email and phone regularly to not miss interview appointments.
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