MS in Computer Science, Machine Learning, or a related field, or equivalent practical experience Minimum 4+ years of research experience in Multi-Modal LLM training and evaluation Proven track record in multimodal SFT plus at least one of distillation, preference optimization, or online RL, backed by shipped models or rigorous experiments Strong programming skills in Python and at least one deep learning, framework, such as JAX or PyTorch. PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience Experience in GRPO, DPO, Vision-OPD, and visual-token compression Publications in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV) Bonus: Experience in quantization, on-device models and SLM (Small Language Model).