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Open nowPosted 58 days ago

AI Applied Scientist

Verily77 open roles

Pay
$219,000 – $246,000 a year
Where
San Bruno California
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Your applicationOpen nowAI Applied ScientistVerily · San Bruno California

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The clock on this job

Early applications get read.

12.7% of postings close within 7 days. Measured by our own scanner across the market. Verily postings stay open a median of 52 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.5%3 days
  3. 12.7%7 days
  4. 20.4%14 days
  5. 35.6%30 days
  6. 58.7%60 days
This job: posted 58 days ago

Verily median: 52 days open

The posting

Who We Are

Verily Health is a data platform and technology company purpose-built to power AI-enabled precision health solutions that accelerate research and improve care for individuals and communities. Uniquely positioned at the intersection of technology, data science, and healthcare, Verily transforms multimodal health data into insights, models, and actions that make healthcare more personalized, predictive, and precise.

Description

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. In this role, you will be responsible for a balanced blend of designing scalable pipelines to curate Electronic Health Records (EHR) and claims data, and conducting advanced research into foundational healthcare models and intelligent multi-agent conversational architectures. You will apply frontier Large Language Models (LLMs) and advanced machine learning techniques to extract deep clinical meaning from messy, unstructured medical text, turning fragmented healthcare data into trustworthy, analysis-ready longitudinal datasets. Your work will directly ground our autonomous care agents and clinical decision support tools in robust, real-world clinical datasets, driving the next generation of healthcare transformation.

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. 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.

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