Qualifications
- Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science,
Software Engineering, Information Technology, or a related quantitative field
- Strong foundation in mathematics, statistics, and machine learning principles
- Relevant certifications in AI/ML, Cloud (Azure, AWS, GCP), or Data Engineering are a plus
- English proficiency in line with Techcombank's policy
Work Experience
- 8+ years of experience in AI/ML, data engineering, and software development, with proven delivery of end-to-end AI solutions in production environments
- Strong expertise in AI specialization, including machine learning, deep learning, NLP, and LLM applications, RAG with hands-on experience in experimentation, model evaluation, and performance tuning
- Demonstrated experience in designing and building scalable AI systems and architectures, including microservices-based solutions and distributed systems
- Solid experience in data engineering for AI, including building ETL/ELT pipelines, data lakes/warehouses, and handling structured & unstructured data using tools like Spark, Kafka, Airflow, and SQL/NoSQL databases
- Proficiency in programming languages such as Python, Go, Java, or Scala, and experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, / JAX, transformers, fine-tuning (LoRA, DPO), distillation, evaluation.)
- Experience in AI experimentation & evaluation, including A/B testing, model benchmarking, validation techniques, and monitoring model performance in production
- Working knowledge of AI Safety, Ethics & Responsible AI, Red-teaming, model risk management, alignment with SBV, MAS, Basel III, ensuring fairness, transparency, explainability, and compliance with regulatory requirements
- Experience in MLOps/LLMOps practices (Level 2), including model deployment, CI/CD pipelines, versioning, and monitoring (e.g., Kubernetes, GPU orchestration, vector DBs, CI/CD for ML, drift and bias monitoring.)
- Proven ability in business needs analysis, translating business problems into AI-driven solutions and measurable outcomes
- Experience managing stakeholders, collaborating with cross-functional teams (business, risk, IT), and influencing decision-making
- Track record of delivering AI projects end-to-end using Agile methodologies, ensuring timelines, quality, and business impact
- Exposure to emerging technologies and research trends in AI, with the ability to evaluate and adopt new approaches when relevant
- Basic experience or potential in AI strategy development and leadership, including mentoring junior team members and contributing to capability building