About the job
About Us
At Hippocratic AI, we are at the forefront of generative AI in the healthcare sector. Our innovative platform excels in facilitating safe, autonomous clinical conversations with patients, utilizing our proprietary LLMs within the Polaris constellation, achieving an unparalleled accuracy rate of over 99.9%.
Why You Should Join Us
Lead the Revolution in Healthcare AI. We are developing the world’s first healthcare-specific, safety-centric LLM, aimed at significantly enhancing patient outcomes worldwide. This is an opportunity to be part of a groundbreaking initiative.
Collaborate with Visionaries. Co-founded by CEO Munjal Shah and a team of esteemed professionals including physicians, hospital executives, AI innovators, and researchers from prestigious institutions like Johns Hopkins and Stanford, you will be working alongside the best minds shaping the future of healthcare.
Join Our Well-Backed Venture. We recently secured a $126M Series C funding round, elevating our valuation to $3.5B with total funding reaching $404M, supported by top-tier investors such as Avenir Growth and a16z.
Be Part of a Transformative Team. Work with experts dedicated to advancing healthcare, improving care quality, and pioneering technologies that make a real difference.
Location Requirement
We believe that collaboration fosters innovation. This role requires you to be present at our Palo Alto office five days a week to cultivate a strong team culture.
About the Role
As a Senior Applied Scientist, you will oversee the RL-based post-training pipeline to enhance our models' clinical reasoning, safety, and alignment in healthcare applications. Your contributions will directly impact millions of patients across various clinical contexts.
Your Responsibilities
- Design and refine RL-based post-training strategies including RLHF, RLVR, and DPO.
- Develop and assess reward models, verifiers, and LLM-as-judge systems.
- Create conversational AI environments and simulations for healthcare RL training utilizing synthetic data.