Full-Time

Director of Machine Learning

Confirmed live in the last 24 hours

Rad AI

Rad AI

51-200 employees

AI-driven software for radiology workflows

AI & Machine Learning
Healthcare

Expert

Remote in USA

Category
Applied Machine Learning
Natural Language Processing (NLP)
AI & Machine Learning
Required Skills
Data Science
Natural Language Processing (NLP)
Requirements
  • Ph.D. or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field.
  • 10+ years of experience in Machine Learning.
  • 5+ years in leadership roles, including 3+ years managing managers.
  • Proven track record of leading high-performing machine learning teams and delivering complex AI solutions.
  • Strong technical expertise in natural language processing, extensively working with large language models.
  • Excellent communication and interpersonal skills, with the ability to effectively communicate technical concepts to both technical and non-technical stakeholders.
  • Deep understanding of machine learning algorithms, neural networks, and natural language processing.
  • Proven track record of successfully delivering generative AI projects from inception to deployment.
  • Demonstrated ability to drive innovation, foster a culture of collaboration, and deliver results in a fast-paced, dynamic environment.
  • Excellent problem-solving skills, strategic thinking, and a proactive approach to challenges.
Responsibilities
  • Provide strategic direction and leadership to Machine Learning teams, fostering a culture of innovation, collaboration, and continuous improvement within the AI/ML department.
  • Drive the design, development, and deployment of cutting-edge generative models and AI solutions.
  • Ensure best practices in the delivery of high-quality data management, model training, validation, and deployment.
  • Work closely with executives and stakeholders to influence and steer the strategic direction of the company's AI initiatives, with a particular focus on generative AI.
  • Recruit, onboard, and mentor top engineering and research talent, building a high-performing team capable of delivering world-class AI solutions.
  • Act as a key point of contact for internal and external stakeholders, providing updates on project status, addressing concerns, and managing expectations.
  • Communicate complex technical concepts to non-technical stakeholders, ensuring alignment and understanding to drive business value and enhance customer experiences.

Rad AI enhances radiology workflows using artificial intelligence to improve efficiency and accuracy in medical imaging. Its main product, Omni Reporting, automates routine tasks and ensures follow-up on incidental findings, making reporting more accurate for radiologists. Unlike competitors, Rad AI focuses specifically on integrating AI into existing radiology practices, providing a subscription-based model that allows for continuous software updates. The company's goal is to streamline healthcare processes while maintaining high standards of data security and patient privacy, as evidenced by its SOC 2 Type II and HIPAA certifications.

Company Stage

Series B

Total Funding

$76.8M

Headquarters

San Francisco, California

Founded

2018

Growth & Insights
Headcount

6 month growth

15%

1 year growth

44%

2 year growth

105%
Simplify Jobs

Simplify's Take

What believers are saying

  • Strategic collaboration with AGFA HealthCare enhances workflow and reduces radiologist burnout.
  • 48% increase in radiograph reporting efficiency at Radiology Associates of North Texas.
  • $83M in funding indicates strong investor confidence and growth potential.

What critics are saying

  • Emerging competition from companies like DeepMind advancing AI in healthcare.
  • Rapid AI technology evolution may require continuous updates to remain competitive.
  • Potential resistance from medical community due to AI-driven automation replacing radiologists.

What makes Rad AI unique

  • Rad AI integrates AI with FHIRcast for enhanced radiology workflow interoperability.
  • Omni Reporting recognized as Best New Radiology Software by AuntMinnie.
  • Early adoption of generative AI and proprietary LLMs for radiology documentation.

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