Machine Learning Engineer

At Hippocratic AI, we offer the opportunity to work with a world-class team of researchers and engineers solving complex challenges through advanced Generative AI technologies and applying this work to the Healthcare domain. We are looking for a Machine Learning Engineer to contribute to the development of Large Language Models (LLMs) and other cutting-edge AI systems for healthcare applications.

In this role, you will collaborate with experts to build and optimize Machine Learning (ML) systems that advance the safety, efficiency, and capability of generative AI solutions. This includes working on the technical design, experimentation, and optimization of AI models aimed at conversational intelligence for healthcare, leveraging both deep learning and traditional ML techniques.

Responsibilities:

• Develop, fine-tune, and deploy state-of-the-art machine learning models for language understanding and generation.

• Research and integrate the latest in LLM technologies with traditional ML methods to improve model accuracy and efficiency.

• Design and implement machine learning pipelines using technologies like LangChain for building multi-agent systems and dynamic decision-making frameworks.

• Optimize model deployment and efficiency through distributed computing and performance scaling.

• Collaborate with the team on reinforcement learning, instruction tuning, and continual learning to enhance the adaptability of LLMs.

• Engage in domain-specific specialization of models, focusing on healthcare-related tasks while ensuring privacy and safety measures.

• Conduct rigorous testing and analysis to evaluate model performance, focusing on real-world healthcare applications.

Required Qualifications

• Master's or PhD in Computer Science, Electrical Engineering, or a related field.

• Proven experience in machine learning and NLP (Natural Language Processing) with applied knowledge of building LLMs (Large Language Models).

• Experience  coding in Python and experience with deep learning frameworks such as TensorFlow, PyTorch, and familiarity with HuggingFace, LangChain, or Deepspeed.

• Experience in developing models using autoregressive language models (GPT-x, Mistral, LLaMA, etc.).

• Knowledge of traditional machine learning methods (e.g., decision trees, SVM, etc.) and experience with model optimization.

• Expertise in large-scale data processing, distributed systems, and cloud services like AWS or GCP.

• Familiarity with healthcare or life sciences applications is a plus.

Preferred Skills

• Experience with LangChain or similar frameworks for orchestrating LLM applications.

• Familiarity with RLHF (Reinforcement Learning from Human Feedback) techniques.

• Understanding of data privacy, especially in healthcare, and compliance with relevant regulations (HIPAA, etc.).

About Hippocratic AI

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, 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, and Greycroft.