AI / Machine Learning Engineer, Healthcare AI

Take a Seat Tech; Boston, Northern (MA, KY); Hybrid; USD 150,000 - 185,000; Full time

Benefits offered by this job

Equity

US benefits package

Hybrid work in Boston

Job summary

Take a Seat Tech in Boston is seeking a hands-on machine learning engineer to move clinical models from prototype to production within healthcare workflows. You will design, train and ship models on clinical and operational data, building end-to-end data pipelines and monitoring to keep systems trustworthy at the point of care.

You will work with clinicians and product teams to ensure model outputs are safe, explainable and defensible in regulated settings, using Python and cloud ML

Qualifications

• Strong Python and modern ML tooling experience, production-focused
• Experience with cloud ML infrastructure and MLOps practices
• Healthcare data exposure welcome but not essential; clinical curiosity matters
• Comfort working in a regulated environment where model decisions must be defensible

Responsibilities

• Design, train and ship machine learning models against clinical and operational data
• Take ownership of the full lifecycle: data pipelines, feature engineering, evaluation, deployment and monitoring
• Collaborate with clinicians and product to ensure model outputs are safe, explainable and usable at the point of care
• Build evaluation and drift monitoring to keep deployed models trustworthy

Skills

Python

ML tooling

MLOps

Regulated environment experience

Tools

Cloud ML platforms

Monitoring tools

Job description

This is a hands-on machine learning engineering role inside a Boston healthcare AI company, taking clinical models from prototype into production use inside health system workflows.

What you will do

• Design, train and ship machine learning models against clinical and operational healthcare data.
• Take ownership of the full lifecycle: data pipelines, feature engineering, evaluation, deployment and monitoring.
• Work alongside clinicians and product to make sure model output is safe, explainable and usable at the point of care.
• Build the evaluation and drift monitoring that keeps deployed models trustworthy.

What we are looking for

• Strong Python plus modern ML tooling, with production experience rather than notebook-only work.
• Experience with cloud ML infrastructure and MLOps practice.
• Healthcare data exposure is welcome but not essential. Clinical curiosity matters more than a healthcare CV.
• Comfort working in a regulated environment where model decisions need to be defensible.

Package

• $150,000 to $185,000 base, plus equity, plus a full US benefits package. Hybrid in Boston.