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Leadership

Director of AI/ML

Bayesian Health · United States · full-time · Remote

Leadershipfull-timeRemoteUnited States
Data Science & AnalyticsDirector
RemoteJobs editorial overview

Strategic Overview

Director of AI/ML at Bayesian Health is a leadership opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.

The published role emphasizes work such as Team Leadership : Build, mentor, and scale a world-class AI/ML team, establishing technical standards, career development frameworks, and a culture of excellence and ownership. Technical Vision & Infrastructure : Define and execute the ML roadmap while…

The role is listed for United States with remote working arrangement, giving candidates the practical context needed to assess fit before applying. Relevant signals in the listing include Data Science & Analytics, Director.

Job seeker snapshot

Key information at a glance

Role focusLeadership
LocationUnited States
WorkplaceRemote
Employmentfull-time
Experience8+ years
PostedOct 18, 2026
Last seenOct 21, 2026
Role context

About This Role

Bayesian Health's mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We're a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data.

We're funded by top tier tech and biotech investors: Andreessen Horowitz, American Medical Association's venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year. Read more about our recent publication in Nature Medicine that associates our products…

What the role delivers

Key Responsibilities & Objectives

  • Team Leadership : Build, mentor, and scale a world-class AI/ML team, establishing technical standards, career development frameworks, and a culture of excellence and ownership.
  • Technical Vision & Infrastructure : 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.
  • Hands-On Modeling & Evaluation: Contribute directly to critical modeling, evaluation, and analysis work, from studies to model performance experiments, ensuring the team ships high-quality ML systems that deliver measurable clinical impact.
  • Cross-Functional Partnership : 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.
Candidate blueprint

Required Qualifications & Candidate Blueprint

  • 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.
Compensation & benefits

Salary & Benefits

The available source data does not publish a numerical salary range for this opening. We do not estimate or substitute third-party figures.

  • Lead Bayesian Health's AI/ML organization with a hands-on, scrappy approach: setting technical vision, rolling up your sleeves on critical modeling work, and building a world-class team that ships breakthrough ML products saving lives in hospitals nationwide.
  • Technical Vision & Infrastructure : 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.
Employer-provided source content

Full Job Description

The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.

Director of AI/ML

In Brief

  • We're an early-stage startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives.

  • Lead Bayesian Health's AI/ML organization with a hands-on, scrappy approach: setting technical vision, rolling up your sleeves on critical modeling work, and building a world-class team that ships breakthrough ML products saving lives in hospitals nationwide.

Who We Are

Bayesian Health's mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We're a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data.

We're funded by top tier tech and biotech investors: Andreessen Horowitz, American Medical Association's venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year. Read more about our recent publication in Nature Medicine that associates our products with lives saved.

What you'll do

As Director of AI/ML, you'll 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. You'll partner deeply with Engineering to architect scalable data warehousing and ML infrastructure that enables rapid model development and reliable production deployment. At our stage, you'll also roll up your sleeves on critical IC work: prototyping models, evaluating system performance, and debugging production issues. This role requires thriving in scrappy, early-stage environments where you're building the plane while flying it, translating clinical needs into technical roadmaps, and getting your hands dirty to ship breakthrough healthcare products.

Responsibilities

  • Team Leadership: Build, mentor, and scale a world-class AI/ML team, establishing technical standards, career development frameworks, and a culture of excellence and ownership.

  • Technical Vision & Infrastructure: 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.

  • Hands-On Modeling & Evaluation: Contribute directly to critical modeling, evaluation, and analysis work, from studies to model performance experiments, ensuring the team ships high-quality ML systems that deliver measurable clinical impact.

  • Cross-Functional Partnership: 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.

Minimum qualifications

  • 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.

Preferred qualifications

  • Experience leading ML organizations through 0-1 product development in healthcare or clinical settings, thriving in environments with limited tooling and infrastructure.

  • Hands-on experience with clinical data standards (HL7, FHIR, EHR) and healthcare ML challenges including data quality, time-series forecasting, and anomaly detection.

  • Strong technical background in data platform architecture, including modern data warehousing solutions (Snowflake, Databricks, Redshift), streaming data systems, and ML infrastructure tools.

  • Track record of publishing research, speaking at conferences, or contributing to the broader ML community while delivering business results.

  • You bring passion and enthusiasm to your work, and are excited to join a growing team to Get Stuff Done and save lives!

Bayesian Health provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

RemoteJobs original analysis

Editor’s Market Perspective (Our Custom Analysis)

Why This Position Matters

This leadership opening is a useful opportunity for candidates whose experience matches Data Science & Analytics, Director. Its strongest career signal is the scope of the work itself — particularly Team Leadership : Build, mentor, and scale a world-class AI/ML team, establishing technical standards, career development frameworks, and a culture of excellence and ownership. — rather than a generic title alone.

Resume & Application Strategy

For the application, mirror the employer's language where it truthfully matches your background: foreground Data Science & Analytics, Director, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.

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We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.