Staff AI Applied Scientist

About the role

As an AI Applied Scientist, you will occupy a unique, highly impactful position that sits at the intersection of our real-world data (RWD) curation mission and our cutting-edge AI Agent development.

Responsibilities

• Design, develop, and deploy advanced generative AI workflows and multi-agent conversational architectures (e.g., using LangGraph) to power personalized user interactions and automated symptom triage.
• Implement, build on, and augment existing LLM/NLP tools to automate the abstraction of high-priority clinical variables and derived features from unstructured medical text, maximizing data completeness and accuracy.
• Develop automated evaluation pipelines and "LLM-as-a-judge" grading rubrics to continuously benchmark agent safety, accuracy, factuality, and compliance across model updates, enabling self-optimization cycles.
• Handle real-world data challenges from clinical and remote settings, ensuring absolute safe data boundaries, privacy preservation, and rigorous technical validation before production releases.
• Communicate highly technical results, methods, and evaluation frameworks clearly via presentations and well-structured reports to both technical and non-technical cross-functional audiences.

Requirements

• Master’s degree in a quantitative discipline (e.g., Data Sciences, Computer Science, Biomedical Informatics, Statistics, Applied Mathematics, or equivalent practical experience).
• Minimum of 3 years of industry experience applying advanced machine learning, NLP, and generative AI techniques (supervised/unsupervised learning, prompt engineering, agentic workflows) to clinical or healthcare datasets.
• Direct experience working with and curating real-world data (such as EHRs or medical claims), with a deep understanding of the complexities and limitations of unstructured medical text.
• Strong proficiency in Python and standard scientific computing/deep learning libraries (e.g., PyTorch, TensorFlow).

Qualifications

• PhD degree in a quantitative discipline (e.g., Computer Science, Biomedical Informatics, Machine Learning, or related field) preferred.
• Familiarity with advanced agent orchestration frameworks (e.g., LangGraph) and foundation model pre-training stacks (e.g., NVIDIA NeMo, Parabricks).
• Familiarity with standard medical terminologies, vocabularies, and ontologies (e.g., SNOMED-CT, LOINC, RxNorm, ICD-10) and healthcare data models (FHIR, OMOP).
• Experience working closely with clinical subject matter experts to establish ground truth benchmarks and adjudicate complex data abstraction guidelines.
• Strong track record of scientific excellence, including peer-reviewed publications or submitted patents in healthcare AI/ML.

Skills

• Advanced machine learning, NLP, and generative AI techniques.
• Experience with real-world data curation and unstructured medical text.
• Python programming and deep learning libraries.
• Experience with advanced agent orchestration frameworks and foundation model pre-training stacks.
• Knowledge of standard medical terminologies, vocabularies, and ontologies.
• Experience working with clinical subject matter experts.
• Strong communication and presentation skills.

Benefits

This role is eligible for Verily-sponsored immigration support. The US base salary range for this full-time position is $254,500 - $286,500 + bonus + equity + benefits.