Applied AI Scientist — Health Diagnostics for ARPA-H

Valiant Harbor International, LLC; Washington (District of Columbia); Presencial; USD 120.000 - 180.000; Jornada completa

Descripción de la vacante

Valiant Harbor International, LLC in the United States, seeks an Applied AI Scientist to support AI diagnostics for rare diseases under ARPA-H PHO. The role focuses on technical guidance across data curation, model training, evaluation, and deployment in clinical settings.

The candidate will review ML proposals, guide model development, and ensure rigor, reproducibility, and real-world applicability. Strong communication and collaboration with clinical SMEs are essential for success in this

Formación

• Masters or PhD in Computer Science, ML, Data Science, or related field.
• 5+ years of experience in a related field.
• Experience applying advanced ML methods (LLMs, deep learning) to health datasets.
• Familiarity with clinical/biomedical data types (EHR, imaging, genomics).
• Ability to review, critique and guide AI/ML work at a high level.
• Strong evaluation knowledge: robustness, fairness, interpretability, reproducibility.

Responsabilidades

• Review and evaluate AI/ML proposals and deliverables from external teams.
• Provide guidance on model development, training methods, and validation strategies.
• Advise on integration of multimodal health data (EHR, imaging, genomic, patient-reported).
• Assess alignment of model architectures with program goals and clinical use cases.
• Evaluate benchmarking results and provide feedback on methodological soundness.
• Advise on deployment considerations, including interpretability, reliability, safety.

Conocimientos

ML in healthcare

Model evaluation

Technical guidance

Technical writing

Educación

Master’s or PhD in CS/ML/DS

Descripción del empleo

Valiant Harbor International, LLC in the United States, seeks an Applied AI Scientist to support AI diagnostics for rare diseases under ARPA-H PHO. The role focuses on technical guidance across data curation, model training, evaluation, and deployment in clinical settings.

The candidate will review ML proposals, guide model development, and ensure rigor, reproducibility, and real-world applicability. Strong communication and collaboration with clinical SMEs are essential for success in this