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# Director of AI/ML

Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move.

[Apply for this job](#job-application)[View company](https://jobicy.com/company/bayesian-health.md)Share17 Sep 2026Published38Listing views4Application actions17 Oct 2026Apply before  Opportunity details

## About this role.

AI SummaryBayesian Health is seeking a hands-on Director of AI/ML to set technical strategy and lead an early-stage healthcare machine learning organization. The role combines people leadership with direct work on model prototyping, evaluation, production debugging, and scalable ML infrastructure. The leader will partner with engineering, product, and clinical stakeholders to translate care workflows into reliable, high-impact ML products. Candidates need a Ph.D., extensive experience shipping ML systems, and proven leadership in resource-constrained startup environments, ideally involving clinical data and regulated healthcare use cases.

## Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

### Job Complexity

5/5EasyHard

### Pace & Pressure

5/5RelaxedFast-paced

### Autonomy Level

5/5GuidedFull ownership

### Communication Load

5/5IndependentCollaborative

AI insightThis is a senior 0-to-1 leadership role requiring deep production ML expertise, healthcare domain judgment, infrastructure architecture skills, and team-building ability. The director must also remain hands-on while operating in a fast-moving, resource-constrained startup environment where model quality can affect patient outcomes.

## Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate$230,000US market range$190k–$300k0$330k

AI insightNo salary was disclosed in the posting. Estimated US yearly base-salary market range for a remote Director of AI/ML in an early-stage healthcare technology company is $190,000-$300,000, with an estimated midpoint of $230,000; equity and variable compensation may be additional.

## Core skills

Skills and capabilities most closely associated with this opportunity.

[Machine Learning](https://jobicy.com/jobs?search_keywords=Machine%20Learning.md)[Artificial Intelligence](https://jobicy.com/jobs?search_keywords=Artificial%20Intelligence.md)[ML Leadership](https://jobicy.com/jobs?search_keywords=ML%20Leadership.md)[Healthcare AI](https://jobicy.com/jobs?search_keywords=Healthcare%20AI.md)[Clinical Data](https://jobicy.com/jobs?search_keywords=Clinical%20Data.md)[MLOps](https://jobicy.com/jobs?search_keywords=MLOps.md)[Data Infrastructure](https://jobicy.com/jobs?search_keywords=Data%20Infrastructure.md)[Model Monitoring](https://jobicy.com/jobs?search_keywords=Model%20Monitoring.md)[Data Warehousing](https://jobicy.com/jobs?search_keywords=Data%20Warehousing.md)[Team Building](https://jobicy.com/jobs?search_keywords=Team%20Building.md)

Sample interview questionsHow would you define an AI/ML strategy for an early-stage healthcare company with limited infrastructure?I would begin with the highest-value clinical decisions and define measurable patient, workflow, and business outcomes. I would prioritize a small number of production-ready use cases, establish data-quality and evaluation foundations, then build reusable platform capabilities such as feature pipelines, monitoring, and deployment workflows as product needs validate them.

How do you evaluate whether a clinical ML model is ready for deployment?

I evaluate technical performance alongside clinical utility, calibration, subgroup performance, robustness to data shifts, and workflow fit. Before release, I would use retrospective validation, prospective or silent-mode testing where feasible, clinician review, clear escalation paths, and post-deployment monitoring for drift, safety signals, and real-world impact.

Describe your approach to building and scaling an ML team in a scrappy startup.

I hire versatile practitioners who can work across modeling, data, and production concerns, while establishing clear ownership and high technical standards. I create lightweight processes for design reviews, experimentation, reproducibility, and career development, then add specialization only when recurring needs justify it.

How would you design infrastructure for real-time healthcare predictions?

I would design around reliable ingestion from EHR and clinical-data sources, standardized patient and event representations, validated feature computation, low-latency serving, and strong observability. The platform should include lineage, access controls, auditability, model versioning, rollback mechanisms, and monitoring appropriate for a regulated setting.

How do you communicate model limitations to clinicians, customers, and investors?

I tailor the level of detail to the audience but remain precise about intended use, performance, uncertainty, limitations, and monitoring plans. For clinicians, I focus on workflow implications and actionable interpretation; for customers and investors, I connect validated performance and safety controls to measurable clinical and operational outcomes.

### Director of AI/ML

### In Brief

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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.

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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

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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.

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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.

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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.

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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

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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

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Proven track record building and scaling high-performing data science and ML engineering teams in resource-constrained, scrappy environments.

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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.

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Experience working with healthcare or similarly regulated industries where model decisions have high-stakes real-world consequences.

### Preferred qualifications

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

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

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

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

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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.

Show more

[Apply now >](https://jobicy.com/jobs/153513-director-of-ai-ml.md)

>  Annual salary information is not provided for this position. Explore salary ranges for similar roles in our [Salary Directory ›](https://jobicy.com/salaries.md)

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