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. And 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.
Qualifications
Minimum Qualifications
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).
Preferred Qualifications
PhD degree in a quantitative discipline (e.g., Computer Science, Biomedical Informatics, Machine Learning, or related field).
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.
This role is eligible for Verily-sponsored immigration support.
The US base salary range for this full-time position is $219,000 - $246,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.
Verily Health Inc. is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you'd like more information on your EEO rights under the law, please click here.
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
