VP of Data Science at Rad AI

Seattle, Washington, United States

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Not SpecifiedCompensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Artificial IntelligenceIndustries

Requirements

10+ years of experience in data science, ML, or applied research roles, with 5+ years in technical leadership roles
Demonstrated success leading teams that built and deployed production AI at scale in real-world user-facing applications
Hands-on experience with LLMs, transformers, and modern ML stacks (e.g. PyTorch, JAX, TensorFlow, Hugging Face, LangChain)
Strong knowledge of cloud-native data and ML platforms (e.g., BigQuery, Spark, Ray, Airflow, KubeFlow)
Proven ability to manage infrastructure as well as applied ML science
Excellent communication skills, with the ability to influence both executive stakeholders and technical teams
Experience building and deploying models to both B2C and B2B experiences that touches tens of millions if not more
Experience with GenAI, Retrieval, ML or Recommendations
Advanced degree (MS or PhD) in Computer Science, ML, Statistics, or related field preferred

Responsibilities

Lead and grow a cross-functional data organization spanning research science, ML, and analytics
Recruit, mentor, and develop managers and ICs across functions, fostering a collaborative and high-performance culture
Create clear development paths and career opportunities for a diverse and deeply technical team
Define and drive our long-term AI/ML roadmap, ensuring alignment with product and business goals
Balance forward-looking research with delivering impactful, scalable product features
Represent the data science org to executive stakeholders and help shape company-wide priorities
Oversee the design and optimization of data infrastructure and real-time ML systems, including ranking, summarization, RAG, LLM orchestration, and signal processing
Drive best practices for model experimentation, evaluation, deployment, observability, and responsible AI
Enable a flexible, high-velocity experimentation environment that empowers scientists and engineers to move quickly
Partner closely with Product, Engineering, Design, and GTM teams to integrate AI deeply into our user experience
Translate technical capabilities into product innovation and measurable business value
Serve as a thought leader for AI both internally and externally (optional: speaking, publishing, or open-source contributions)

Skills

Key technologies and capabilities for this role

AIMachine LearningData ScienceData EngineeringMLOpsRAGLLM OrchestrationSummarizationRankingReal-time MLData Infrastructure

Questions & Answers

Common questions about this position

What salary is offered for the VP of Data Science role?

This information is not specified in the job description.

Is this VP of Data Science position remote or office-based?

This information is not specified in the job description.

What experience and skills are required for this role?

Candidates need 10+ years in data science, ML, or applied research, including 5+ years in technical leadership, success leading teams deploying production AI at scale, and hands-on experience with LLMs, transformers, and modern ML stacks like PyTorch, JAX, TensorFlow, Hugging Face, and LangChain.

What is the company culture like at Read AI?

The role involves fostering a collaborative and high-performance culture, creating clear development paths and career opportunities for a diverse and deeply technical team.

What makes a strong candidate for the VP of Data Science position?

A strong candidate has demonstrated success leading teams that built and deployed production AI at scale in user-facing applications, with hands-on expertise in LLMs and modern ML stacks, plus experience balancing research with scalable product features.

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