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 and Computer Science or related fields
• At least 3 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 in API development using 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 have 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
MB Bank requires applicants to provide the following detailed information:
- Personal information: Full name, Date of birth, Gender
- Phone number and Email contact
- Educational background, School graduated from
- Work experience
- 3 - 5 outstanding skills
- Recruitment source
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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