Applied ML Engineer at Knowtex

This role is ideal for a mid-to-senior level Engineer (3–7+ years) who thrives at the intersection of machine learning research and production software engineering. You should have a deep mastery of Python and PyTorch, with a proven track record of moving generative AI models beyond the notebook and into low-latency, high-throughput production environments. The most compelling aspect of this position is the opportunity to work at a high-growth startup founded by Stanford AI scientists. While an exact salary isn't listed, the package includes "meaningful equity," which offers significant upside potential as the platform scales across federal and commercial health systems. You’ll be solving complex technical challenges like model quantization and distributed inference while making a tangible impact on clinician burnout. **You might be a good fit if you...** * Have extensive experience deploying transformer-based LLMs or speech-to-text systems on AWS. * Are comfortable building automated evaluation pipelines to ensure model reliability in high-stakes healthcare settings. * Enjoy the "applied" side of ML—optimizing for speed, batching, and caching rather than just training. * Prefer a hybrid work environment in San Francisco and want to work on a product with clear social utility.