Staff Machine Learning Engineer, Applied Science

Sorry, this job was removed at 10:08 p.m. (CST) on Thursday, Feb 26, 2026
Palo Alto, CA
In-Office
Artificial Intelligence • Healthtech
The Role
About Us

Hippocratic AI is the leading generative AI company in healthcare. We have the only system that can have safe, autonomous, clinical conversations with patients. We have trained our own LLMs as part of our Polaris constellation, resulting in a system with over 99.9% accuracy.

Why Join Our Team

Reinvent healthcare with AI that puts safety first. We’re building the world’s first healthcare‑only, safety‑focused LLM — a breakthrough platform designed to transform patient outcomes at a global scale. This is category creation.

Work with the people shaping the future. Hippocratic AI was co‑founded by CEO Munjal Shah and a team of physicians, hospital leaders, AI pioneers, and researchers from institutions like El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, Meta, Microsoft, and NVIDIA.

Backed by the world’s leading healthcare and AI investors. We recently raised a $126M Series C at a $3.5B valuation, led by Avenir Growth, bringing total funding to $404M with participation from CapitalG, General Catalyst, a16z, Kleiner Perkins, Premji Invest, UHS, Cincinnati Children’s, WellSpan Health, John Doerr, Rick Klausner, and others.

Build alongside the best in healthcare and AI. Join experts who’ve spent their careers improving care, advancing science, and building world‑changing technologies — ensuring our platform is powerful, trusted, and truly transformative.

Location Requirement

We believe the best ideas happen together. To support fast collaboration and a strong team culture, this role is expected to be in our Palo Alto office five days a week, unless otherwise specified.

About the Role

Staff Machine Learning Engineers at Hippocratic AI are foundational to the design, deployment, and optimization of cutting-edge ML systems powering our next-generation, safety-focused generative AI for healthcare. You’ll work closely with research scientists and product teams to build scalable infrastructure and models that support robust, real-time, and personalized conversational AI capabilities.

We are seeking an experienced Staff Machine Learning Engineer to lead the development of machine learning pipelines, contribute to training and inference systems for Large Language Models (LLMs), and drive the productionization of ML models that directly impact healthcare delivery and patient outcomes. This role is both strategic and hands-on, perfect for someone excited about technical leadership in a fast-paced, mission-driven environment.

What You'll Do

Our engineering challenges include:

  • Designing scalable, high-performance infrastructure for LLM training, fine-tuning, and inference

  • Building ML pipelines and tooling for experimentation, evaluation, and deployment

  • Optimizing model performance and efficiency in production environments

  • Collaborating cross-functionally to integrate ML solutions into end-user applications

  • Maintaining compliance with healthcare standards of safety, privacy, and reliability

What You Bring

Must-Have:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field; PhD is a plus

  • 7+ years of industry experience building and deploying ML systems, ideally with focus on LLMs or deep learning

  • Strong software engineering skills and experience developing in Python

  • Deep experience with ML frameworks like PyTorch or TensorFlow

  • Familiarity with distributed training frameworks (e.g., DeepSpeed, FSDP, Horovod)

  • Proven experience designing, implementing, and scaling ML pipelines for large models

  • Experience with cloud platforms (e.g., AWS, GCP, Azure) and container orchestration (e.g., Kubernetes, Docker)

  • Exposure to healthcare, clinical, or life sciences data is a strong plus

Nice-to-Have:

  • Strong preference for individuals who can work onsite at our HQ located in Palo Alto, CA, but we will consider candidates throughout the U.S.

As a Staff ML Engineer at Hippocratic AI, you’ll have a seat at the table in technical decision-making, partner closely with product and research leads, and help define the roadmap for scalable, safe ML systems. This role offers the chance to be deeply embedded in a team of engineers and scientists pioneering the future of healthcare-focused AI.

References
  1. Polaris: A Safety-focused LLM Constellation Architecture for Healthcare, https://arxiv.org/abs/2403.13313

  2. Polaris 2: https://www.hippocraticai.com/polaris2

  3. Personalized Interactions: https://www.hippocraticai.com/personalized-interactions

  4. Human Touch in AI: https://www.hippocraticai.com/the-human-touch-in-ai

  5. Empathetic Intelligence: https://www.hippocraticai.com/empathetic-intelligence

  6. Polaris 1: https://www.hippocraticai.com/research/polaris

  7. Research and clinical blogs: https://www.hippocraticai.com/research

Please be aware of recruitment scams impersonating Hippocratic AI. All recruiting communication will come from @hippocraticai.com email addresses. We will never request payment or sensitive personal information during the hiring process.

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The Company
HQ: Palo Alto, California
97 Employees
Year Founded: 2023

What We Do

Hippocratic AI’s mission is to develop the first safety-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, Microsoft, Meta and NVIDIA. Hippocratic AI has received a total of $137 million in funding and is backed by leading investors, including General Catalyst, Andreessen Horowitz, Premji Invest, SV Angel, NVentures (Nvidia Venture Capital), and Greycroft. For more information on Hippocratic AI: www.HippocraticAI.com.

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