Description
Sieve is hiring a Machine Learning Engineer to own the end-to-end machine learning lifecycle for customer-facing video understanding problems. The role involves fine-tuning vision-language and multimodal foundation models, building automated evaluation and quality-assurance pipelines, designing filtering, ranking, retrieval, and labeling systems, creating datasets and benchmarks, and shipping production ML pipelines. The engineer will work directly with frontier AI labs, translate ambiguous requirements into scalable systems, and measure improvements in dataset quality. The position requires strong Python, deep learning, PyTorch, and foundation-model experience, and requires onsite work in San Francisco five days per week.
