Research scientist role focused on designing and building large-scale foundation models for time series demand forecasting. The role involves developing novel architectures, training strategies, and data generation techniques, with a strong emphasis on both scientific research (publications) and production deployment impacting millions of dollars in automated decisions. Experience with transfer learning, zero-shot forecasting, and synthetic data generation is key.

Senior AI/ML researcher to define ML strategy for a healthcare foundation model and inference system, focusing on frontier models, proprietary domain models, and monetizable features under regulatory constraints. Requires expertise in training/adapting large models, distributed training, RLHF/DPO, retrieval, evaluation, and ML systems engineering, with experience in high-stakes/regulated domains.