Building the universal ingestion layer so that messy, unstructured human data becomes machine-readable at scale.
Machine Learning Engineer
Unstructured data is still the hardest problem in enterprise AI. This team is building the bridge between raw human documents and the models that need to understand them, processing millions of complex PDFs, spreadsheets, and images with precision that generic parsers can't touch. As an ML Engineer, you'll design and train models that extract structure from chaos, optimize inference pipelines, and push the frontier of what document understanding actually means in production. You'll work at the intersection of computer vision, NLP, and systems engineering, shipping models that directly unlock revenue for the business.
What they're looking for
- 4+ years of hands-on machine learning experience, with a track record of shipping models to production
- Deep fluency in Python and modern ML frameworks (PyTorch, JAX, or TensorFlow)
- Experience working with vision-language models, document understanding, or structured extraction from unstructured inputs
- Comfortable owning the full model lifecycle: data curation, training, evaluation, deployment, and monitoring
- Strong communication instincts — you explain tradeoffs clearly and collaborate well with infrastructure and product engineers