About Us
Hippocratic AI is developing the first safety-focused Large Language Model (LLM) for healthcare. Our mission is to dramatically improve healthcare accessibility and outcomes by bringing deep healthcare expertise to every person. No other technology has the potential for this level of global impact on health.
About Us
Hippocratic AI is developing the first safety-focused Large Language Model (LLM) for healthcare. Our mission is to dramatically improve healthcare accessibility and outcomes by bringing deep healthcare expertise to every person. No other technology has the potential for this level of global impact on health.
Why Join Our Team
- Innovative mission: We are creating a safe, healthcare-focused LLM that can transform health outcomes on a global scale.
- Visionary leadership: Hippocratic AI was co-founded by CEO Munjal Shah alongside physicians, hospital administrators, healthcare professionals, and AI researchers from top institutions including El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, Meta, Microsoft and NVIDIA.
- Strategic investors: Raised $137 million from top investors including General Catalyst, Andreessen Horowitz, Premji Invest, SV Angel, NVentures (Nvidia Venture Capital), and Greycroft.
- Team and expertise: We are working with top experts in healthcare and artificial intelligence to ensure the safety and efficacy of our technology.
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.
- 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.
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.
References
- Polaris: A Safety-focused LLM Constellation Architecture for Healthcare, Polaris 2: Personalized Interactions: Human Touch in AI: Empathetic Intelligence: Polaris 1: Research and clinical blogs:
Seniority level
Seniority level
Mid-Senior level
Employment type
Employment type
Full-time
Job function
Job function
Research, Analyst, and Information TechnologyIndustries
Hospitals and Health Care
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