AI Research Engineer (Innovation - BBL)

We are seeking a passionate and innovative AI Research Engineer to join our team in advancing the frontiers of Artificial Intelligence. This role focuses on research and development of new AI models in areas such as computer vision, natural language processing, and voice technologies. You will explore cutting-edge techniques in Machine Learning (ML), Deep Learning (DL), and Generative AI (GenAI), contributing to breakthroughs that shape the future of intelligent systems.

Responsibilities

· Conduct research and experimentation to design novel AI models in computer vision, language modeling, and voice technologies.

· Explore and develop new architectures in ML, DL, and GenAI, including transformers, diffusion models, and multimodal systems.

· Investigate and optimize training strategies for large-scale models, including data augmentation, self-supervised learning, and reinforcement learning.

· Collaborate with research scientists, data engineers, and product teams to translate theoretical advances into practical prototypes.

· Publish findings, contribute to patents, and stay at the forefront of academic and industrial AI research.

· Evaluate emerging AI frameworks and orchestration tools (such as LangChain, LangGraph, Crew.ai, OpenAI Agent SDK) for applications.

· Build experimental pipelines to validate hypotheses and benchmark models against state-of-the-art baselines.

· Contribute to the development of scalable infrastructure for training and evaluating large models.

Requirements

· Strong problem-solving and analytical skills with a research-oriented mindset.

· Excellent communication skills to present complex ideas clearly and collaborate across disciplines.

· Solid foundation in machine learning, deep learning, and generative modeling techniques.

· Experience in designing and training advanced architectures (CNNs, RNNs, Transformers, GANs, diffusion models).

· Proficiency in Python and deep learning frameworks such as PyTorch and TensorFlow.

· Familiarity with large-scale training environments using Docker, Kubernetes, and distributed computing.

· Knowledge of data processing frameworks (e.g., Apache Spark) is a plus.

· Hands-on experience with experimental design, quantitative research, and benchmarking AI models.

· Exposure to CI/CD workflows for research pipelines is advantageous.

· A track record of publications, open-source contributions, or patents in AI research is highly desirable.

Location: Bangkok Bank, Head Office, Silom

Contact Person: พี่นุ่มนิ่ม HR 02 685 7852, 063 403 5669