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Bayesian Health

AI-powered clinical data insights platform

Director of AI/ML

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeRemote in USANo salary listed

About the Job

Requirements

  • A Ph.D. in Machine Learning, Computer Science, Statistics, or a related field and at least 8 years of experience shipping machine-learning products, including at least 3 years leading machine-learning teams at early-stage startups.
  • A proven track record of building and scaling high-performing data science and machine-learning engineering teams in resource-constrained environments.
  • Deep technical expertise in production machine-learning 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.

Responsibilities

  • Set the technical vision and strategy for the machine-learning organization while building and leading a high-performing team of data scientists and machine-learning engineers.
  • Build, mentor, and scale an AI/ML team; establish technical standards, career-development frameworks, and a culture of excellence and ownership.
  • Define and execute the machine-learning roadmap; partner with Engineering to architect data-warehousing solutions, machine-learning infrastructure, and data pipelines that enable rapid model prototyping and deployment at scale.
  • Contribute directly to modeling, evaluation, and analysis work, including studies and model-performance experiments, ensuring high-quality machine-learning systems deliver measurable clinical impact.
  • Collaborate with Engineering, Product, and Clinical teams to translate clinical workflows into machine-learning opportunities.
  • Communicate model performance and impact to technical and non-technical stakeholders, including customers and investors.

Desired Qualifications

  • Experience leading machine-learning organizations through 0-to-1 product development in healthcare or clinical settings, particularly in environments with limited tooling and infrastructure.
  • Hands-on experience with clinical data standards including HL7, FHIR, and EHR, and healthcare machine-learning challenges including data quality, time-series forecasting, and anomaly detection.
  • A strong technical background in data-platform architecture, including modern data-warehousing solutions such as Snowflake, Databricks, and Redshift, streaming data systems, and machine-learning infrastructure tools.
  • A track record of publishing research, speaking at conferences, or contributing to the broader machine-learning community while delivering business results.

About the Company

Bayesian Health

AI-powered clinical data insights platform

Bayesian Health uses AI to help hospitals turn raw healthcare data into real-time, actionable insights for clinicians. Its platform continuously analyzes patient data and care workflows to support proactive, higher-quality care, especially for patient outcomes. How it works: a subscription-based platform that integrates with existing hospital systems, processes real-time data, and presents clinicians with actionable insights. It also provides ongoing updates, training, and customization to fit each provider’s needs. How it stands out: it combines rigorous scientific methods with practical AI tools, emphasizes real-time data analysis and proactive care, and offers strong integration and support typical for biotech-grade solutions. Its goal is to improve patient outcomes by enabling care teams to act on timely, data-driven insights inside hospitals.

Company size
11-50
Company stage
Late Stage VC
Total funding
$30.2M
Headquarters
New York City, New York
Founded
Not listed

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