[Remote] Staff ML Research Scientist (Clinical) at Rad AI

United States

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$200,000 – $230,000Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Healthcare, Artificial IntelligenceIndustries

Requirements

MS or PhD (or equivalent research experience) in Computer Science, Electrical Engineering, Computational Linguistics, Biomedical Informatics, or related quantitative field
6+ years of applied ML research experience (industry or academia)
Proven experience building NLP or ML systems for healthcare, clinical documentation, or biomedical applications
Demonstrated fluency with medical terminology and clinical reasoning

Responsibilities

Lead high-impact ML research projects from concept to deployment, focused on clinical NLP and reasoning systems
Define the technical direction of research initiatives within your product area; identifying opportunities to apply state-of-the-art models to real-world radiology workflows
Collaborate deeply with radiologists and clinical experts to understand diagnostic reasoning patterns, report structures, and clinical decision-making criteria—then encode that understanding into robust ML systems
Architect and evaluate models that integrate structured and unstructured medical data (clinical notes, diagnostic criteria, patient context) to enhance diagnostic reasoning and reporting accuracy
Build NLP systems that can parse, reason over, and generate clinically accurate content using medical terminology and ontologies
Mentor and guide other researchers in experimental design, model reproducibility, and technical communication
Advance research infrastructure by contributing to data pipelines, training frameworks, and model evaluation tooling

Skills

Machine Learning

NLP

Clinical AI

Medical AI

Medical Literature

Clinical Terminology

Rad AI

AI-driven software for radiology workflows

About Rad AI

Rad AI enhances radiology workflows using artificial intelligence to improve efficiency and accuracy in radiological practices. Its main product, Omni Reporting, automates routine tasks, ensures follow-up on incidental findings, and improves reporting accuracy. This software integrates seamlessly into existing workflows, making it easier for radiologists to manage their tasks. Unlike competitors, Rad AI emphasizes data security and patient privacy, being SOC 2 Type II and HIPAA certified. The company's goal is to provide reliable AI-driven solutions that streamline healthcare processes and improve patient outcomes.

San Francisco, CaliforniaHeadquarters

2018Year Founded

$76.8MTotal Funding

SERIES_BCompany Stage

AI & Machine Learning, HealthcareIndustries

51-200Employees

Benefits

Health Insurance

Health Savings Account/Flexible Spending Account

401(k) Retirement Plan

Paid Holidays

Remote Work Options

Unlimited Paid Time Off

Risks

Emerging competition from companies like DeepMind could overshadow Rad AI's offerings.

Rapid AI technology evolution requires Rad AI to continuously innovate.

AI-driven automation may face resistance from the medical community.

Differentiation

Rad AI's Omni Reporting won 'Best New Radiology Software' by AuntMinnie.

Rad AI integrates AI with FHIRcast for enhanced radiology workflow interoperability.

Rad AI is a pioneer in using large language models for radiology report generation.

Upsides

Rad AI achieved a 48% increase in radiograph reporting efficiency at RANT.

Rad AI raised $50M in Series B funding, boosting its expansion capabilities.

Strategic collaboration with AGFA HealthCare enhances Rad AI's market position.

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