Ensure infrastructure meets security, compliance, and data residency requirements relevant to Singapore Government systems, including access controls, encryption, and audit logging.
This role has no fixed boundaries. You may shape product definitions, build solutions hands‑on, or support client go‑live — depending on project phase and your strengths. We use the title AI Builder because we seek individuals who can own and deliver an end‑to‑end initiative with the power of AI.
Design and implement a digital chain-of-custody framework that captures assurance records including mill certificates, fabrication data, inspection results and carbon footprint information.
Responsible for the development of deep learning and operations research models and related intelligent systems for the supply chain and logistics of the global E-Commerce business.
This is a start up-style role with broad ownership across AI development, data collection, robot integration, testing, failure analysis, and continuous performance improvement. The ideal candidate is comfortable working across disciplines and taking ideas from early experimentation through to real-robot deployment.
We are looking for a hands-on Embodied AI Engineer with experience in robot learning to develop, fine-tune, deploy, and validate intelligent behaviors on physical humanoid robots.
Construct multimodal semantic links across video-product, product-product, and video-video relationships to support trend understanding, product mining, AIGC generation, and content-commerce supply optimization.
Master's degree or above, with at least 3 years of hands-on experience in Reinforcement Learning (RL), Reinforcement Learning from Human Feedback (RLHF), or Reinforcement Learning with Verifiable Rewards (RLVR). Experience in Agent-related projects is preferred.
Master's degree or above, with at least 3 years of hands-on experience in Reinforcement Learning (RL), Reinforcement Learning from Human Feedback (RLHF), or Reinforcement Learning with Verifiable Rewards (RLVR). Experience in Agent-related projects is preferred.
Design and implement RAG pipelines and LLM application workflows (prompting, retrieval, tool calling, agents), and expose them as reliable, scalable services.
Use simulation and digital twins to model production flows, equipment behavior, and system constraints, and to safely test and refine agent strategies before deployment.