AI​/Machine Learning Engineer

Healthcare AI and Machine Learning Engineer Jobs USA

AI and machine learning engineering roles across US health technology: clinical documentation, imaging, risk models, triage support and operational automation. Salary, location and working model appear on every vacancy where the employer has confirmed them.

The clinician, supported by AI. Judgement kept human.

What does a Health Tech AI / Machine Learning Engineer do?

A healthcare AI or machine learning engineer builds, evaluates and operates models on clinical, claims or imaging data. The role covers model development and the surrounding safety work: dataset governance, bias and performance evaluation, human review design, and production monitoring for drift.

Confidential client Boston, Massachusetts Hybrid

Pay

Healthcare AI and machine learning engineers in the United States typically earn $135,000 to $175,000, rising to roughly $170,000 to $220,000 at senior level and above $210,000 at staff level.

AI / Machine Learning Engineer salary bands in the United States

A healthcare AI or machine learning engineer builds, evaluates and operates models on clinical, claims or imaging data. The role covers model development and the surrounding safety work: dataset governance, bias and performance evaluation, human review design, and production monitoring for drift.

Model quality is rarely the constraint in health AI. Access to representative data, evaluation against clinical ground truth, and defensible monitoring usually determine whether a system reaches production. US teams often work across large language model applications for documentation and administrative workload alongside traditional predictive models.

Assessment

• Python plus a modern ML stack, including LLM application tooling
• Evaluation design against clinical ground truth, not just offline metrics
• Working with EHR, claims, imaging or device data at scale
• MLOps: reproducible training, versioning, drift and performance monitoring
• De-identification, PHI governance and data access controls
• Awareness of FDA expectations where a model is part of a regulated device

Market

• Employers now separate applied LLM engineering from classical predictive modelling in job specs.
• Evaluation and monitoring experience is weighted heavily in shortlisting.
• Clinical validation exposure is the most common gap in otherwise strong candidates from other industries.

Also searched as: AI Engineer healthcare, Machine Learning Engineer healthcare, ML Engineer health, Healthcare AI Engineer.

FAQ

Enough to interpret labels and failure modes. You need to understand where data comes from, how clinicians will use the output, and what a harmful error looks like. Formal clinical training is not required.

It depends on the claim. Software supporting clinical decisions can fall under FDA device regulation, while administrative and documentation tools generally do not. The distinction drives how much validation and documentation the role carries.

Machine learning engineers from other data-rich industries, and data scientists inside health systems or payers who move to the vendor side.

Product Manager Software Engineer Data Scientist Healthcare Data Analyst Account Executive Customer Success Manager Typical AI / Machine Learning Engineer pay in the United States: $170,000 to $220,000.