Job Description

Overview

Applied Scientists at Hippocratic provide a dynamic opportunity to work with a team of world-class research scientists and engineers, who are pursuing scientific and technical innovation to help solve complex challenges through the use of Generative AI technology.

We are seeking Artificial Intelligence (AI) Applied Scientists to join our team and contribute to the development of Large Language Models (LLMs) aimed at creating disruptive safety-focused generative intelligence for Healthcare. As an Applied Scientist, you will play a crucial role in developing, improving, and exploring the capabilities of LLMs to solve complex real-world problems geared towards building Conversational AI products. Our ongoing research areas encompass but are not limited to:

• Post-training: Instruction tuning and reinforcement learning from human and AI feedback.

• Multilinguality: Post-training LLMs to talk fluently in any language, with medical accuracy and safety.

• Continual Learning: Enabling LLMs to evolve and adapt over time and learn from previous experiences over human interactions.

• Specialization: Tailoring LLMs to meet domain-specific requirements.

• Efficiency: Optimizing the computational efficiency and cost-effectiveness of LLM deployments.

Required Qualifications

• PhD in Computer Science, Electrical Engineering, or related field.

• 5+ years of industry experience in NLP and machine learning, with a focus on LLMs.

• Strong programming skills in Python.

• Experience with deep learning frameworks such as PyTorch or TensorFlow.

• Experience with large-scale data processing and distributed computing.

• Experience with training (pre-training / fine-tuning / RLHF / post-training) autoregressive language models like LLaMA, GPT-x, etc.

• Experience with open-source LLM platforms and training stack (e.g., HuggingFace, Deepspeed etc.).

• Experience in healthcare or life sciences is a plus.

Other Requirements

Strong preference for individuals that can work onsite in our HQ located in Palo Alto, CA, but will consider individuals throughout the U.S.

Applied Scientists are directly responsible for improving the product, safety, and intelligence of our system by researching innovative AI solutions and applying them into our models. Collaborating with accomplished doctoral candidates and some of the industry's brightest minds, Applied Scientist partake in an ongoing learning journey that fosters collaboration and establishes enduring connections. This position not only facilitates individual career advancement but also plays a crucial role in propelling forward innovative research and development initiatives.

Why Join Our Team

• Innovative Mission: We are developing a safe, healthcare-focused large language model (LLM) designed to revolutionize health outcomes on a global scale.

• Visionary Leadership: Hippocratic AI was co-founded by CEO Munjal Shah, alongside a group of physicians, hospital administrators, healthcare professionals, and artificial intelligence researchers from leading institutions, including El Camino Health, Johns Hopkins, Stanford, Microsoft, Google, and NVIDIA.

• Strategic Investors: We have raised a total of $278 million in funding, backed by top investors such as Andreessen Horowitz, General Catalyst, Kleiner Perkins, NVIDIA’s NVentures, Premji Invest, SV Angel, and six health systems.

• World-Class Team: Our team is composed of leading experts in healthcare and artificial intelligence, ensuring our technology is safe, effective, and capable of delivering meaningful improvements to healthcare delivery and outcomes.

For more information, visit .

We value in-person teamwork and believe the best ideas happen together. Our team is expected to be in the office five days a week in Palo Alto, CA unless explicitly noted otherwise in the job description

References

1. Polaris: A Safety-focused LLM Constellation Architecture for Healthcare,
   2 . Polaris 2:
   3 . Personalized Interactions:
   4 . Human Touch in AI:
   5 . Empathetic Intelligence:
   6 . Polaris 1:
   7 . Research and clinical blogs:

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