Director of AI/ML

🕒 January 10

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Bayesian Health

WebsiteLinkedInAll Job Openings

11 - 50 employees

🤖 Artificial Intelligence

⚕️ Healthcare Insurance

🧬 Biotechnology

Artificial Intelligence • Healthcare Insurance • Biotechnology

Bayesian Health is a healthcare technology company that focuses on transforming healthcare data into actionable clinical insights through its adaptive AI platform. The platform enables Intelligent Care Augmentation, allowing caregivers to deliver proactive and higher quality care, ultimately resulting in improved patient health outcomes. With a foundation of extensive research in the field, Bayesian Health aims to empower physicians and care teams with real-time data to enhance decision-making and save lives.

📋 Description

• Set the technical vision and strategy for Bayesian Health's machine learning organization while building and leading a high-performing team of data scientists and ML engineers. • Partner deeply with Engineering to architect scalable data warehousing and ML infrastructure that enables rapid model development and reliable production deployment. • Roll up your sleeves on critical IC work: prototyping models, evaluating system performance, and debugging production issues. • Build, mentor, and scale a world-class AI/ML team, establishing technical standards, career development frameworks, and a culture of excellence and ownership. • Define and execute the ML roadmap while partnering closely with Engineering to architect data warehousing solutions, ML infrastructure, and data pipelines that enable the team to rapidly prototype and deploy models at scale. • Contribute directly to critical modeling, evaluation, and analysis work, ensuring the team ships high-quality ML systems that deliver measurable clinical impact. • Collaborate with Engineering, Product, and Clinical to translate complex clinical workflows into ML opportunities, and communicate model performance and impact to technical and non-technical stakeholders including customers and investors.

🎯 Requirements

• Ph.D. in Machine Learning, Computer Science, Statistics, or related field with 8+ years shipping ML products, and 3+ years leading ML teams at early stage startups • Proven track record building and scaling high-performing data science and ML engineering teams in resource-constrained, scrappy environments. • Deep technical expertise in production ML systems and data infrastructure, including hands-on experience with data warehousing, real-time prediction, model monitoring, and performance evaluation. • Experience working with healthcare or similarly regulated industries where model decisions have high-stakes real-world consequences.

🏖️ Benefits

• Equal employment opportunities • Prohibits discrimination and harassment of any type