This paper presents an overview of the recent developments in pile foundation engineering within the Vietnamese context. The review focus is on the three key directions: (i) The development for analyzing bi-directional static load tests, using data specific to the unique geotechnical conditions prevalent in Vietnam. It aims to refine and advance existing techniques, tailoring them to the distinct characteristics of the region. (ii) An exploration of the load-bearing characteristics between super-long large bored piles and barrette piles. It seeks to understand the performance and behavior of these two foundation types by focusing on their distinctive features and influencing factors. (iii) An investigation into the transformative potential of machine learning in shaping the landscape of pile foundation engineering, as well as the framework for constructing valuable research in machine learning techniques, as furnished by real-world field data derived from the diverse terrains of Vietnam. In essence, this paper seeks to provide researchers and practitioners with a roadmap for appreciating the potential of machine learning in enhancing the efficacy and precision of pile foundation studies.