4+ years as a software engineer, data engineer, or AI/ML practitioner writing technical design documents, data pipeline documentation, or API specifications
Architecture Design: Lead the architecture design and implementation of video generation post-training, focusing on high-quality instruction data, preference alignment, and video quality enhancement.
Build, tailor, and operate AI agents and assistants for internal functions, owning features end-to-end from design through deployment and production operation (including testing and CI/CD).
The Technical Track (Senior AI Engineer / Tech Lead): Command deeper architectural ownership, pioneer core AI strategies, and drive high-stakes technical decisions, or the
Fresh grads or final year students in Computer Science, Engineering, Data Science or related field. Candidates from other backgrounds with strong hands-on AI projects are welcome.
Develop and optimise model quantization algorithms, including post-training quantization (PTQ), quantization-aware training (QAT), and related compression techniques.
Lead Technical Deployments: Drive end-to-end technical deployments for GPU neocloud and AI Factory customers, from initial bare metal configuration to a validated vCluster environment.
Domain Authority: Serve as the semiconductor domain expert for the Eureka Materials Agent, ensuring technical accuracy and industrial practicability for chip, device, and material reverse engineering scenarios.
In response to the expansion into new emerging areas in recent years, the ASTM Critical and Emerging Technologies (CET) Division is exploring the convergence of Additive Manufacturing and other emerging technologies such as Robotics, automation and autonomous system, Artificial intelligence and Machine learning (AI &ML) targeting towards applications in Advanced Manufacturing.
Build core Agent logic, including but not limited to task planning and orchestration, tool calling, multi-turn dialogue management, memory, RAG, context engineering, and multi-agent collaboration.