About the role

AI/ML Engineer building intelligent and adaptive systems for digital banking at Qode's Client. Involves working on production ML models and collaborating in a hybrid team.

Responsibilities

Design, build, and optimize AI/ML pipelines for real-time and batch inference, leveraging modern MLOps practices.
Collaborate with data engineers and software developers to integrate models into the banking platform, ensuring reliability, monitoring, and version control.
Research, prototype, and productionize models in areas such as credit scoring, fraud detection, transaction classification, personalization, and conversational AI.
Implement robust model evaluation, A/B testing, and drift detection frameworks to ensure accuracy and stability over time.
Contribute to internal frameworks and libraries to standardize ML development workflows across teams.
Explore and evaluate emerging techniques in LLMs, Generative AI, and reinforcement learning applicable to the ecosystem.
Mentor junior engineers and collaborate closely with product and infrastructure teams to ensure model readiness for global scale.

5+ years of hands-on experience in machine learning engineering, data science, or related software development roles.
Proven experience deploying and maintaining ML models in production environments (preferably in fintech, e-commerce, or large-scale consumer products).
Technical Skills:
Strong proficiency in Python and core ML libraries (TensorFlow, PyTorch, Scikit-learn, XGBoost, etc.).
Solid understanding of algorithms, data structures, and distributed computing concepts.
Experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow, Docker, Kubernetes, CI/CD pipelines).
Familiarity with data engineering stacks such as Spark, Kafka, and cloud data warehouses (e.g., BigQuery, Redshift).
Strong understanding of model monitoring, versioning, and observability in live systems.
Experience with cloud environments (AWS, GCP, or Azure) and IaC (Terraform, CloudFormation) is a plus.
Familiarity with secure data handling and compliance within regulated environments (e.g., banking or financial data) is advantageous.
Mindset:
A system-thinking approach to ML development, viewing models as part of a continuous delivery ecosystem.
Curiosity for applied AI research balanced with pragmatism for production constraints.
Strong communication skills and ability to collaborate in cross-functional and multi-country teams

Meal and parking allowance
Benefits and salary rank during probation
Insurances as Vietnamese labor law and premium health care for you and your family
Performance bonus up to 2 months
13th month salary
15-day annual leave+ 3-day sick leave + 1 birthday leave + 1 Christmas leave
Work-life balance 40-hr per week from Mon to Fri
Opportunity to build large-scale AI systems that power global digital banking across multiple markets.
Work in a cloud-native, event-driven, and API-first architecture with cutting-edge technologies.
Join a team where AI is not an experiment; it's a core part of the platform strategy.
Hybrid working model, strong engineering culture, and continuous learning environment (LLMs, MLOps, data observability, and more).
Be part of a global technology organization with shared ownership and impact.