Hippocratic AI
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:
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.
Team and expertise:
We are working with top experts in healthcare and artificial intelligence to ensure the safety and efficacy of our technology.
For more information, visit www.HippocraticAI.com.
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.
About the role
Build the next generation of voice agents
Work with an interdisciplinary team
Develop a highly scalable infrastructure for LLM processing
Responsibilities
Develop and maintain scalable backend systems to support high-performance AI applications in healthcare.
Collaborate with cross-functional teams, including data scientists and ML engineers, to design and build efficient data pipelines for large-scale healthcare datasets.
Build and manage APIs and microservices that enable smooth data retrieval, processing, and interaction with AI models.
Monitor and improve backend systems to optimize performance, reliability, and uptime.
Work closely with product managers to understand healthcare requirements and help transform them into technical solutions.
Develop and optimize backend infrastructure supporting data ingestion, feature extraction, and tagging workflows.
Implement tag management and metadata systems to streamline dataset organization and retrieval.
Contribute to end-to-end ML workflows, integrating data preparation, training, evaluation, and deployment into reproducible pipelines.
Qualifications Must-Have:
Bachelor’s degree in Computer Science, Computer Engineering, or a related field. (Master's is preferred)
2-5+ years of experience in backend development using programming languages like Python, Golang, or similar.
Experience building and maintaining multi-modal data pipelines (speech, vision, and text) using Ray or Apache Airflow for distributed processing and model experimentation.
Distributed computing with Spark, Hadoop, or similar.
Familiarity with relational database systems and RESTful APIs.
Basic understanding of cloud infrastructure (e.g. AWS, GCP).
Preferred:
Exposure to AI/ML concepts or experience working with LLMs.
Experience working in teams that handle sensitive or regulated data.
Familiarity with gRPC, graphQL or similar.
Exposure to DevOps concepts - CI/CD, deployment, terraform, build systems.
Experience with data science.
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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:
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.
Team and expertise:
We are working with top experts in healthcare and artificial intelligence to ensure the safety and efficacy of our technology.
For more information, visit www.HippocraticAI.com.
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.
About the role
Build the next generation of voice agents
Work with an interdisciplinary team
Develop a highly scalable infrastructure for LLM processing
Responsibilities
Develop and maintain scalable backend systems to support high-performance AI applications in healthcare.
Collaborate with cross-functional teams, including data scientists and ML engineers, to design and build efficient data pipelines for large-scale healthcare datasets.
Build and manage APIs and microservices that enable smooth data retrieval, processing, and interaction with AI models.
Monitor and improve backend systems to optimize performance, reliability, and uptime.
Work closely with product managers to understand healthcare requirements and help transform them into technical solutions.
Develop and optimize backend infrastructure supporting data ingestion, feature extraction, and tagging workflows.
Implement tag management and metadata systems to streamline dataset organization and retrieval.
Contribute to end-to-end ML workflows, integrating data preparation, training, evaluation, and deployment into reproducible pipelines.
Qualifications Must-Have:
Bachelor’s degree in Computer Science, Computer Engineering, or a related field. (Master's is preferred)
2-5+ years of experience in backend development using programming languages like Python, Golang, or similar.
Experience building and maintaining multi-modal data pipelines (speech, vision, and text) using Ray or Apache Airflow for distributed processing and model experimentation.
Distributed computing with Spark, Hadoop, or similar.
Familiarity with relational database systems and RESTful APIs.
Basic understanding of cloud infrastructure (e.g. AWS, GCP).
Preferred:
Exposure to AI/ML concepts or experience working with LLMs.
Experience working in teams that handle sensitive or regulated data.
Familiarity with gRPC, graphQL or similar.
Exposure to DevOps concepts - CI/CD, deployment, terraform, build systems.
Experience with data science.
#J-18808-Ljbffr