Description
DataRobot is hiring a post-doctoral research-engineering intern to design, implement, train, and evaluate a multi-target joint probabilistic foundation model. The role focuses on temporal, tabular, mixed-modality, and state-space architectures, distributional output heads, decoding schemes, controlled experiments, and scalable PyTorch implementations. Candidates should have strong PyTorch and probabilistic modeling experience; knowledge of stochastic processes, stochastic differential equations, synthetic-data generation, and quantitative domains is a strong plus. The internship offers exposure to research, production-quality implementation, and real deployment constraints.
