Machine Learning Engineer

Analyze model failures; Build dataset pipelines; Create model evaluation suites; Develop labeling workflows; Develop tooling for experiment tracking and model comparison; Improve data quality; Package models with documentation and reproducible evaluations; Run hyperparameter and architecture experiments; Track benchmarks across model versions; Train and fine tune models on curated datasets; Translate findings into dataset improvements;