Hippocratic AI
Staff Machine Learning Engineer, Applied Science
Hippocratic AI, Stanford, California, United States, 94305
Overview
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. Youll 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. 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
Required Qualifications
Bachelors or Masters 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
Other Requirements
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, youll 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. 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, NVIDIAs 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 www.HippocraticAI.com. #J-18808-Ljbffr
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. Youll 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. 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
Required Qualifications
Bachelors or Masters 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
Other Requirements
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, youll 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. 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, NVIDIAs 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 www.HippocraticAI.com. #J-18808-Ljbffr