Sieve

Sieve is seeking a Member of Technical Staff, Applied Research to join their team. In this role, you will train and evaluate multimodal models, focusing on video generation and audiovisual understanding, to understand how data influences model capabilities. You will own the research process end-to-end, from identifying model weaknesses and forming hypotheses to building experiments and evaluating results. This involves fine-tuning models, developing reproducible training and evaluation pipelines, and conducting controlled experiments on data quality and supervision. The ideal candidate enjoys bridging research and engineering, implementing methods, debugging training runs, and ensuring findings are reliable and impactful for data sourcing, curation, and usage.

$150k - $350k

As a Machine Learning Engineer at Sieve, you will be responsible for the entire ML lifecycle. This includes understanding customer problems, designing datasets, improving models, building evaluation systems, and deploying production pipelines that demonstrably enhance dataset quality. You will collaborate directly with leading AI labs to address complex data challenges and develop end-to-end systems to solve them. Your work might involve fine-tuning multimodal models for specific use cases, engineering vision-language model (VLM) QA pipelines, designing new evaluation frameworks, or managing large-scale filtering processes on extensive multimodal datasets. We are seeking engineers who are adept at taking ownership of problems from initial customer requirements through to the deployment of production ML systems that yield measurable improvements in dataset quality.

$150k - $350k