AI Research – Financial Foundation Models

MS Capital is a private fund management company with a strong founding team with long-accumulated experience in strategy modelling, trading system and platform development. Using advanced artificial intelligence technology as the cornerstone, and enforcing strict investment management, the company's investment fund has gained sustained and stable returns.You will be joining MS Capital's technology arm, with AL/ML as its cornerstone, and is committed to providing users with high-quality and stable trading services. The company now has a number of experienced quantitative researchers, world-class deep learning scientists and engineers from leading internet companies and top universities. The company has also provided various kinds of trading solutions for a number of leading brokerage firms and organizations. The company's vision is to integrate artificial intelligence technology with quantitative investment scenarios, relying on strong artificial intelligence R&D capabilities and advanced trading strategy models, to provide users with comprehensive and stable investment service.We are dedicated to breakthrough research in the core technologies of large models and are looking for talented individuals with research experience and strong interest in following areas:Model Architecture & ScalingResearch and develop next-generation foundation model architecturesMoE architecture, routing, sparse activation, and load balancingAttention architecture and optimization, including efficient and sparse attentionTokenization, embeddings, and representation learningExplore new architectures and scaling approaches beyond standard TransformersLarge-Scale Pre-trainingImprove model pre-training efficiency, stability, and scalabilityOptimize training recipes, data pipelines, and large-scale experimentationDevelop efficient parallelism strategies across large GPU clustersImprove memory efficiency, training throughput, and GPU utilizationAI Systems & Performance EngineeringOptimize distributed training, networking, data loading, and fault toleranceDevelop and optimize high-performance GPU kernelsWork with CUDA, Triton, Pallas, CuTe, XLA, or lower-level PyTorch/JAX where applicableCo-design model architectures and training systems for maximum performanceSkills & Qualifications:Master / PhD in Computer Science, Artificial Intelligence, Mathematics, or related fields;Research experiences in MoE/MHA/Tokenization, with published papers (preferably in top conferences) or in-depth research projects.Proficient in frameworks such as PyTorch/JAX, with experience in large model training and fine-tuning;Deep understanding of Transformer architectures, with experience for related source code (e.g., Megatron, DeepSpeed);Familiarity with distributed training and memory optimization is a plus;Strong academic curiosity + Engineering mindset for practical implementation + Self-driven exploration.Interested applicants please apply directly here or send your resume to hr@mscapital.sg