Research Engineer, Speech Technologies

Hippocratic AI’s mission is to develop the first safest focused Large Language Model (LLM) for healthcare. The company believes that a safe LLM can dramatically improve healthcare accessibility and health outcomes in the world by bringing deep healthcare expertise to every human. No other technology has the potential to have this level of global impact on health.

The company was co-founded by CEO Munjal Shah, alongside a group of physicians, hospital administrators, healthcare professionals, and artificial intelligence researchers from El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, and Nvidia. Hippocratic AI has received a total of $120M in funding and is backed by leading investors, including General Catalyst, Andreessen Horowitz, Premji Invest, and SV Angel

We are currently hiring a Research Engineer to focus on Speech technologies.

Responsibilities:

• Design and implement speech recognition decoder leveraging existing libraries such as Kaldi, OpenFST, etc.

• Work closely with scientists and other engineers to enable features such as custom vocabulary recognition, LM rescoring, etc.

• Own the end-to-end development, testing, and deployment of the ASR decoder.

Basic Qualifications:

• PhD or Master’s degree with 5+ years of experience in building speech recognition decoders/libraries leveraging Kaldi/OpenFST.

• Experience with FSTs/WFSTs, etc.

• Hands-on experience with developing decoder modules (for RNN-Ts, E2E models, etc.) using Kaldi, including Beam search and Kaldi parameter tuning.

• Strong programming skills with hands-on experience in C++.

• Comfortable working in a Linux/Unix command-line environment.

• Team player with good communication skills (oral and written).

Preferred Qualifications:

• Experience with 0 to 1 development of decoders for Speech Recognition for E2E and RNN-T models in Kaldi.

• Experience with rescoring logic and LLM decoders.

• Experience with CUDA and enabling batch processing audio on GPUs for ASR tasks.