[Skip to main content](#main-content) [OpenNash Jobs](https://jobs.opennash.com/) [Hiring report](/reports/hiring/) · [All Rakuten jobs](https://jobs.opennash.com/companies/rakuten/) · [Search jobs](/search/) Rakuten · Singapore # EDB-IPP Project: Advancing GPU Optimization for Large Language Models Singapore Operations Listed on Rakuten’s official careers site. Listed as of October 19, 2026. Check that it is still open and apply there. [Apply on Rakuten’s careers site →](https://rakuten.wd1.myworkdayjobs.com/RakutenAsia/job/Singapore/EDB-IPP-Project--Advancing-GPU-Optimization-for-Large-Language-Models_1031282) [OpenNash Jobs](https://jobs.opennash.com/) / [Rakuten](https://jobs.opennash.com/companies/rakuten/) / EDB-IPP Project: Advancing GPU Optimization for Large Language Models ## Job description ### Job Description Rakuten Asia, in partnership with the Economic Development Board ( EDB) through the Industrial Postgraduate Programme ( IPP), is seeking new PhD students. We are looking for individuals with a robust understanding of deep learning, machine learning, and natural language processing to contribute to our innovative research projects. Essential requirements include proven hands-on expertise and strong engineering skillsets, specifically in the development and training of PyTorch models. IPP Programme Benefits Candidates successfully selected for this programme will receive full sponsorship for their postgraduate studies and will be hired by Rakuten Asia upon successful completion. Collaboration Model The collaboration will include joint PhD student supervision, shared access to computational resources for large-scale model compression experiments, and regular research exchanges. Output will include high-impact publications, open-source tools, and demonstrable prototypes of efficient AI. Project Outline Introduction Rakuten is committed to advancing the frontier of AI infrastructure, with a strong focus on optimizing large-scale GPU clusters for training and serving Large Language Models (LLMs). As models grow in size and complexity—ranging from dense architectures to mixture-of-experts (MoE)—achieving efficiency across training, inference, and deployment has become increasingly critical. Our GPU Optimization department combines deep system expertise and significant computational assets, and we are seeking strategic collaborations with leading universities to jointly tackle these challenges. Proposed Research Areas We propose collaborative research in the following areas, with flexibility to refine topics based on mutual expertise: Efficient Scheduling for Sparse & Dense LLMs: Design token-aware, load-balanced scheduling algorithms for MoE and hybrid LLM workloads that reduce inter-GPU communication and optimize heterogeneous cluster utilization. Efficient Inference for State Space Models Develop high-throughput, low-latency inference techniques for state space models, leveraging their linear-time properties to outperform traditional attention mechanisms in long-context scenarios. Memory-Aware Training & Serving Explore advanced quantization, memory-efficient checkpointing, offloading strategies, and dynamic memory management techniques to support training and inference of ultra-large models. Scalable Parallelism for LLMs Investigate hybrid parallelism (data, model, pipeline, expert) and communication-reduction strategies tailored for scaling LLMs across thousands of GPUs. Hardware-Aware Optimization Develop compiler, kernel, and data layout optimizations that fully exploit features of modern GPU architectures, improving throughput for both dense and sparse model operations. High-Throughput, Low-Latency Inference Create optimized model serving strategies using speculative decoding, continuous batching, expert routing, and adaptive computation for production-grade LLM applications. Rakuten is an equal opportunities employer and welcomes applications regardless of sex, marital status, ethnic origin, sexual orientation, religious belief or age. ## At a glance - Posted by the employer: Not stated - First seen by OpenNash: Oct 12, 2026 - Last checked: Oct 19, 2026 - Listed for: 7 days - Location: Singapore[Apply on Rakuten’s careers site →](https://rakuten.wd1.myworkdayjobs.com/RakutenAsia/job/Singapore/EDB-IPP-Project--Advancing-GPU-Optimization-for-Large-Language-Models_1031282) ## More jobs at Rakuten ### [EDB-IPP Project: Advancing Domain-Specific Multimodal Large Language Models and AI Governance for Vertical Domain Applications](https://jobs.opennash.com/companies/rakuten/jobs/c8c74387aa58f4aa0e6c/) Singapore ### [EDB-IPP Project: Personalization and Long-Context Modeling in Large Language Models](https://jobs.opennash.com/companies/rakuten/jobs/f3222fb1634d390b3888/) Singapore ### [Senior Project Manager](https://jobs.opennash.com/companies/rakuten/jobs/66f4f75bd4c894003e65/) Singapore ### [(Rakuten Advertising) Client Services Manager](https://jobs.opennash.com/companies/rakuten/jobs/034dc891b1bdf67e0c7a/) Singapore ### [(Rakuten Advertising) Consultant, Advanced Analytics](https://jobs.opennash.com/companies/rakuten/jobs/473d75eda951940db10e/) Singapore ## Similar jobs at other companies ### [Join BeOne Cell Therapy — Advancing Next-Generation Allogeneic Cell Therapy](https://jobs.opennash.com/companies/beone-medicines/jobs/1252db49a00f61190186/) BeOne Medicines · Taipei Neihu ### [Everyday Banking (EDB) Consultant](https://jobs.opennash.com/companies/anz-group-holdings/jobs/73736a488e9fc1beb41e/) ANZ Group Holdings · Quezon City, PH ### [Operations Executive (IPP)](https://jobs.opennash.com/companies/deutsche-post/jobs/241c454c8cd20ea94975/) Deutsche Post · INDORE, Madhya Pradesh, India ### [IPP Solution Architect](https://jobs.opennash.com/companies/rockwell-automation/jobs/6b68feb9e030dc4af5c9/) Rockwell Automation OpenNash lists jobs from employers’ own careers sites and does not handle applications. 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