STEP

STEP: Career-path recommendation system using LLMs, temporal GRU, and contrastive occupation embeddings

Researchers introduce STEP (Sequential Trajectory of Employment Prediction), a career-path recommendation system that extracts structured trajectory data from unstructured resumes using LLMs and models it with a time-decay GRU, FiLM conditioning on educational attainment, and attention-based pooling. They also introduce ROUTE, a two-stage contrastive pretraining procedure for multilingual occupation embeddings. STEP is evaluated on four career-trajectory datasets including an improved version of the public JobHop dataset, outperforming prior baselines on next-job prediction. Code and data are publicly released.